Method and apparatus for determining a probability of colorectal cancer in a subject

ABSTRACT

A method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer is disclosed. The method comprises, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

This application claims the benefit of U.S. provisional application 61/123,798, filed Apr. 10, 2008 and of U.S. provisional application 61/123,831, filed Apr. 11, 2008. The entire contents of both provisional applications are incorporated by reference herein.

TECHNICAL FIELD

The disclosure relates to apparatuses, kits and methods for determining a probability of colorectal cancer in a test subject. More particularly, the disclosure relates to apparatuses, kits and methods for diagnosing colorectal cancer in a test subject by measuring a level of one or more gene products in blood of the test subject.

BACKGROUND

Colorectal cancer causes 655,000 deaths worldwide per year, making it the second-leading cause of cancer-related deaths. It is the third most frequently diagnosed cancer in men and women in the United States and carries an overall population lifetime risk of 6%. (American Cancer Society. Cancer Facts and Figures. 2008. Atlanta: American Cancer Society.). The American Cancer Society estimates that about 108,070 new cases of colon cancer (53,760 in men and 54,310 in women) and 40,740 new cases of rectal cancer (23,490 in men and 17,250 in women) will be diagnosed in 2008. Of those diagnosed, nearly half are expected to die within five years. In the United States in 2008 an estimated 50,000 men and women will die of cancer of the colon and rectum. (American Cancer Society 2008). This high mortality rate is due at least in part to the fact that a large proportion of cancers are detected at relatively late stages, such as following onset of overt symptoms, when the cancer is more difficult to treat. In addition, identification of colorectal cancer at later stages concomitantly necessitates harsher treatment, such as radical colostomy. It has been shown that the identification and treatment of colorectal cancer at earlier stages significantly reduces the risk of developing more advanced disease, and hence risk of death from the disease. Stage at detection is critically related to patient survival. Localized cancers (Dukes's Stage A or B) have an excellent prognosis of 82%-93% at five years. Regional (Dukes's Stage C) patients have a five year survival rates of 55% to 60%; and only 5% to 8% of patients with late stage cancer will survive the five year span. (O'Connell J B, Maggard M, Ko C Y. Colon cancer survival rates with the new American Joint Committee on cancer sixth edition staging. JNCI. 2004; 96: 1420-1425.). Therefore, a test to screen for colorectal cancer so as to allow earlier treatment should markedly reduce the incidence of advanced-stage colorectal cancer (Ransohoff D F. Colorectal cancer screening in 2005: status and challenges. Gastroenterology. 2005 May; 128(6):1685-95) and decrease the current costs to the medical system. Thus, the American Cancer Society recommends that all Americans age 50 and older be screened regularly for colorectal cancer. Unfortunately, only a small fraction of the population at risk is screened for the disease (Mitka M. Colorectal cancer screening rates still fall far short of recommended levels. JAMA. 2008 Feb. 13; 299(6):622), as currently available screening methods require insufficiently available and/or costly resources, are associated with unacceptably low patient compliance, and/or are associated with significant health risks.

Currently utilized screening technologies to test for colorectal cancer include fecal occult blood test (FOBT), flexible sigmoidoscopy, double contrast barium enema (DCBE), and colonoscopy. The current recommended standards for screening for colorectal cancer in individuals over the age of 50 and who are considered part of an average risk population include: an FOBT yearly, a sigmoidoscopy every five years, a colonoscopy every ten years and a DCBE every five years. For a high risk population where one or more family members have had colorectal cancer, a colonoscopy is recommended every two years as a follow up to FOBT or sigmoidoscopy. Each of these tests suffers significant disadvantages. Fecal occult blood testing suffers from low sensitivity, requires significant dietary and other restrictions prior to testing and is associated with poor patient compliance. Sigmoidoscopy and colonoscopy are more sensitive than the other standard methods since they involve direct visualization of the lumen of the colon, however these methods are also associated with various significant disadvantages. Sigmoidoscopy and colonoscopy are both highly invasive procedures which cause significant levels of discomfort, causing many individuals to opt not to undergo these recommended screening procedures. Sigmoidoscopy only allows visualization of the distal part of the colon and hence cannot detect a relatively large fraction of cancers, and colonoscopy, despite allowing examination essentially along the entire length of the colon, is associated with a significant failure rate for detection of colorectal cancer. In addition, sigmoidoscopy and colonoscopy are costly, are insufficiently available, and may result in potentially lethal complications, such as accidental intestinal perforation.

Various approaches have been proposed in the prior art for colorectal cancer testing using identification and analysis of markers of this disease in blood (reviewed in Hundt S. et al. Blood markers for early detection of colorectal cancer: a systematic review. Cancer Epidemiol Biomarkers Prey. 2007 October; 16(10):1935-53). Such approaches, if successful, would have the advantage of circumventing critical disadvantages of the standard prior art methods, by virtue, for example, of being relatively non-invasive, minimally cumbersome, essentially risk-free and hence likely to be associated with increased patient screening compliance rates. However, none of these approaches has demonstrated an optimal capacity for diagnosing colorectal cancer.

Thus, there is a longstanding and urgent need for an improved method of determining a probability of colorectal cancer in a subject based on analysis of blood markers.

SUMMARY

The invention discloses novel methods, apparatuses and kits for determining a probability of colorectal cancer in a subject, based on novel blood markers of colorectal cancer. This use can be effected in a variety of ways as further described and exemplified herein.

According to one aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a ANXA3 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to yet another aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a CLEC4D gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to one aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a IL2RB gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to still another aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a LMNB1 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to a further aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a PRRG4 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to yet a further aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a TNFAIP6 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to still a further aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a VNN1 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to further features of the invention described below, the determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject.

According to further features of the invention described below, the method of determining the probability that the human test subject has colorectal cancer as opposed to not having colorectal cancer further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having colorectal cancer, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer.

According to further features of the invention described below, the determining of the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data, wherein the mathematical model is for determining the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the invention there is provided a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to another aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a ANXA3 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to another aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a CLEC4D gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet another aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a IL2RB gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to still another aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a LMNB1 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to a further aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a PRRG4 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet a further aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a TNFAIP6 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to still a further aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a VNN1 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to an additional aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet an additional aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a CLEC4D gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to still an additional aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a IL2RB gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet still an additional aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a LMNB1 gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to another aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a PRRG4 gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet another aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a TNFAIP6 gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to still another aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a VNN1 gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to a further aspect of the present invention there is provided a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and wherein, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to yet a further aspect of the present invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, computer-implemented steps of: applying to test data representing a level of RNA encoded by the gene in blood of the test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a formula for calculating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and wherein, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to one aspect of the invention there is provided a method of diagnosing colorectal cancer in a test subject, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein a determination that the test data corresponds to the positive control data and not to the negative control data provides an indication of colorectal cancer in the test subject.

According to a further aspect of the present invention there is provided a method of diagnosing colorectal cancer in a test subject, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer provides an indication of colorectal cancer in the test subject, and wherein, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer provides an indication of colorectal cancer in the test subject.

According to another aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a annexin A3 (ANXA3) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to yet another aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a C-type lectin domain family 4, member D (CLEC4D) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to still another aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a interleukin 2 receptor, beta (IL2RB) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood.

According to a further aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a lamin B1 (LMNB1) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to yet a further aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a proline rich Gla (G carboxyglutamic acid) 4 (transmembrane) (PRRG4) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to still a further aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a tumor necrosis factor, alpha induced protein 6 (TNFAIP6) gene in the test sample of blood, ii) comparing the level of RNA encoded by as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to still a further aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and i) determining a level of RNA encoded by a vanin 1 (VNN1) gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood.

According to an additional aspect of the present invention there is provided a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: a) obtaining a test sample of blood from the subject; and for each gene of a set of genes selected from the group consisting of: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, i) determining a level of RNA encoded by the gene in the test sample of blood, ii) comparing the level of RNA encoded by the gene of the set as determined in step (i) with the level of RNA encoded by the gene in one or more control samples of blood; and b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood, and concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if, for IL2RB, the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood.

According to an additional aspect of the present invention there is provided a method of diagnosing colorectal cancer in a test subject, comprising: a) obtaining a test sample of blood from the subject; and for each gene of a set of genes selected from the group consisting of: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, i) determining a level of RNA encoded by the gene in the test sample of blood, and ii) applying to the level of RNA encoded by the gene of the set as determined in step (i) and to the level of RNA encoded by the gene in one or more control samples of blood a mathematical formula for generating a value indicating whether, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood, and, for IL2RB, the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood; and b) concluding that there is an indication of colorectal cancer in the test subject, if, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, the value indicates that the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood, and concluding that there is an indication of colorectal cancer in the test subject if, for IL2RB, the value indicates that the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood.

According to further features of the invention described below, the control samples are from individuals who have been diagnosed as not having colorectal cancer.

According to still another aspect of the invention there is provided a kit comprising packaging and containing, for each gene of a set of two or more genes selected from the group consisting of ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, a primer set capable of generating an amplification product of a polynucleotide complementary to RNA encoded, in a human subject, only by the gene.

According to further features of the invention described below, the kit further contains two or more components selected from the group consisting of a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer.

According to further features of the invention described below, the kit further contains at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.

According to further features of the invention described below, the kit further contains a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying a mathematical model to test data representing a level of RNA encoded by the gene in blood of a human test subject, wherein the mathematical model is derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, and wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

According to further features of the invention described below, the kit further contains a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying, to test data representing a level of RNA encoded by the gene in blood of a human test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and wherein, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

According to further features of the invention described below, the set of one or more genes consists of ACTB and one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1.

According to further features of the invention described below, the set of one or more genes consists of ACTB and ANXA3.

According to further features of the invention described below, the set of one or more genes consists of ACTB and CLEC4D.

According to further features of the invention described below, the set of one or more genes consists of ACTB and IL2RB.

According to further features of the invention described below, the set of one or more genes consists of ACTB and LMNB1.

According to further features of the invention described below, the set of one or more genes consists of ACTB and PRRG4.

According to further features of the invention described below, the set of one or more genes consists of TNFAIP6 and PRRG4.

According to further features of the invention described below, the set of one or more genes consists of ACTB and VNN1.

According to further features of the invention described below, the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis.

According to further features of the invention described below, the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method.

According to further features of the invention described below, the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject.

According to further features of the invention described below, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. According to further features of the invention described below, the set of one or more genes consists of IL2RB and one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1.

According to further features of the invention described below, the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject.

According to further features of the invention described below, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

According to further features of the invention described below, the set of one or more genes consists of ANXA3.

According to further features of the invention described below, the set of one or more genes consists of CLEC4D.

According to further features of the invention described below, the set of one or more genes consists of IL2RB.

According to further features of the invention described below, the set of one or more genes consists of LMNB1.

According to further features of the invention described below, the set of one or more genes consists of PRRG4.

According to further features of the invention described below, the set of one or more genes consists of TNFAIP6.

According to further features of the invention described below, the set of one or more genes consists of VNN1.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and ANXA3.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and CLEC4D.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and LMNB1.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and PRRG4.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and TNFAIP6.

According to further features of the invention described below, the set of one or more genes consists of IL2RB and VNN1.

DEFINITIONS

As will become apparent, preferred features and characteristics of one aspect of the invention are applicable to any other aspect of the invention. It should be noted that, as used herein, the singular form “a”, “an” and “the” include plural references unless the context clearly dictates otherwise.

“Encode” A polynucleotide, including a gene, is said the to “encode” a RNA and/or polypeptide if, in its native state or when manipulated by methods well known to those skilled in the art, it can be transcribed and/or translated to produce the mRNA for and/or the polypeptide or a fragment thereof. The anti-sense strand is the complement of such a nucleic acid, and the encoding sequence can be deduced there from.

The term “label” refers to a composition capable Of producing a detectable signal indicative of the presence of the target polynucleotide in an assay sample. Suitable labels include radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means.

As used herein, a “sample” refers to a sample of tissue or fluid isolated from an individual, including but not limited to, for example, blood, plasma, serum, tumor biopsy, urine, stool, sputum, spinal fluid, pleural fluid, nipple aspirates, lymph fluid, the external sections of the skin, respiratory, intestinal, and genitourinary tracts, tears, saliva, milk, cells (including but not limited to blood cells), organs, and also samples of in vitro cell culture constituent.

Examples of amplification techniques include strand displacement amplification, as disclosed in U.S. Pat. No. 5,744,311; transcription-free isothermal amplification, as disclosed in U.S. Pat. No. 6,033,881; repair chain reaction amplification, as disclosed in WO 90/01069; ligase chain reaction amplification, as disclosed in European Patent Appl. 320 308; gap filling ligase chain reaction amplification, as disclosed in U.S. Pat. No. 5,427,930; and RNA transcription-free amplification, as disclosed in U.S. Pat. No. 6,025,134.

Examples of a primer of the invention include an oligonucleotide which is capable of acting as a point of initiation of polynucleotide synthesis along a complementary strand when placed under conditions in which synthesis of a primer extension product which is complementary to a polynucleotide is catalyzed. Such conditions include the presence of four different nucleotide triphosphates or nucleoside analogs and one or more agents for polymerization such as DNA polymerase and/or reverse transcriptase, in an appropriate buffer (“buffer” includes substituents which are cofactors, or which affect pH, ionic strength, etc.), and at a suitable temperature. A primer must be sufficiently long to prime the synthesis of extension products in the presence of an agent for polymerase. A typical primer contains at least about 5 nucleotides in length of a sequence substantially complementary to the target sequence, but somewhat longer primers are preferred.

The terms “complementary” or “complement thereof”, as used herein, refer to sequences of polynucleotides which are capable of forming Watson & Crick base pairing with another specified polynucleotide throughout the entirety of the complementary region. This term is applied to pairs of polynucleotides based solely upon their sequences and does not refer to any specific conditions under which the two polynucleotides would actually bind.

A primer will always contain a sequence substantially complementary to the target sequence, that is the specific sequence to be amplified, to which it can anneal.

In the context of this invention, the term “probe” refers to a molecule which can detectably distinguish between target molecules differing in structure, such as allelic variants. Detection can be accomplished in a variety of different ways but preferably is based on detection of specific binding. Examples of such specific binding include antibody binding and nucleic acid probe hybridization.

The term “gene” as used herein is a polynucleotide which may include coding sequences, intervening sequences and regulatory elements controlling transcription and/or translation. Genes of the invention include normal alleles of the gene encoding polymorphisms, including silent alleles having no effect on the amino acid sequence of the gene's encoded polypeptide as well as alleles leading to amino acid sequence variants of the encoded polypeptide that do not substantially affect its function. These terms also may otpyiosnlly include alleles having one or more mutations which affect the function of the encoded polypeptide's function.

The polynucleotide compositions, such as primers of the invention, of this invention include RNA, cDNA, DNA complementary to target cDNA of this invention or portion thereof, genomic DNA, unspliced RNA, spliced RNA, alternately spliced RNA, synthetic forms, and mixed polymers, both sense and antisense strands, and may be chemically or biochemically modified or may contain non-natural or derivatized nucleotide bases, as will be readily appreciated by those skilled in the art.

Where nucleic acid according to the invention includes RNA, reference to the sequence shown should be construed as reference to the RNA equivalent, with U substituted for T.

The term “amount” or “level” of RNA encoded by a gene of the invention, preferably a colorectal cancer biomarker gene described herein, or a housekeeping gene, encompasses the absolute amount of the RNA, the relative amount or concentration of the RNA, as well as any value or parameter which correlates thereto.

The methods of nucleic acid isolation, amplification and analysis are routine for one skilled in the art and examples of protocols can be found, for example, in the Molecular Cloning: A Laboratory Manual (3-Volume Set) Ed. Joseph Sambrook, David W. Russel, and Joe Sambrook, Cold Spring Harbor Laboratory; 3rd edition (Jan. 15, 2001), ISBN: 0879695773. Particularly useful protocol source for methods used in PCR amplification is PCR (Basics: From Background to Bench) by M. J. McPherson, S. G. Moller, R. Beynon, C. Howe, Springer Verlag; 1st edition (Oct. 15, 2000), ISBN: 0387916008.

“Kit” refers to a combination of physical elements, e.g., probes, including without limitation specific primers, labeled nucleic acid probes, antibodies, protein-capture agent(s), reagent(s), instruction sheet(s) and other elements useful to practice the invention, in particular to identify the levels of particular RNA molecules in a sample. These physical elements can be arranged in any way suitable for carrying out the invention. For example, probes and/or primers can be provided in one or more containers or in an array or microarray device.

Colorectal cancer, also called colon cancer or rectal cancer or colorectal carcinoma, is cancer that forms in either the colon or the rectum.

The present invention is useful in a diagnostic product or method to detect the level of RNA of genes of interest, in particular, the colorectal biomarkers of the present invention. Accordingly, the invention encompasses the use of diagnostic kits based on a variety of methodologies, e.g., PCR, reverse transcriptase-PCR, quantitative PCR, microarray, chip, mass-spectroscopy, which are capable of detecting RNA levels in a sample. The invention also provides an article of manufacturing comprising packaging material and an analytical agent contained within the packaging material, wherein the analytical agent can be used for determining and/or comparing the levels of RNA encoded by one or more target genes of the invention, and wherein the packaging material comprises a label or package insert which indicates that the analytical agent can be used to identify levels of RNA that correspond to a probability that a test subject has colorectal cancer, such as a probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

The present invention therefore provides kits comprising degenerate primers to amplify polymorphic alleles or variants of target genes of the invention, and instructions comprising an amplification protocol and analysis of the results. The kit may alternatively also comprise buffers, enzymes, and containers for performing the amplification and analysis of the amplification products. The kit may also be a component of a screening or prognostic kit comprising other tools such as DNA microarrays. The kit may also provides one or more control templates, such as nucleic acids isolated from sample of patients without colorectal cancer, and/or nucleic acids isolated from samples of patients with colorectal cancer.

The kit may also include instructions for use of the kit to amplify specific targets on a solid support. Where the kit contains a prepared solid support having a set of primers already fixed on the solid support, e.g. for amplifying a particular set of target polynucleotides, the kit also includes reagents necessary for conducting a PCR on a solid support, for example using an in situ-type or solid phase type PCR procedure where the support is capable of PCR amplification using an in situ-type PCR machine. The PCR reagents, included in the kit, include the usual PCR buffers, a thermostable polymerase (e.g. Taq DNA polymerase), nucleotides (e.g. dNTPs), and other components and labeling molecules (e.g. for direct or indirect labeling). The kits can be assembled to support practice of the PCR amplification method using immobilized primers alone or, alternatively, together with solution phase primers.

In one embodiment, the kit provides one or more primer pairs, each pair capable of amplifying RNA encoded by a target gene of the invention, thereby providing a kit for analysis of RNA expression of several different target genes of the invention in a biological sample in one reaction or several parallel reactions. Primers in the kits may be labeled, for example fluorescently labeled, to facilitate detection of the amplification products and consequent analysis of the RNA levels.

In one embodiment, levels of RNA encoded by more than one target gene can be determined in one analysis. A combination kit may therefore include primers capable of amplifying cDNA derived from RNA encoded by different target genes. The primers may be differentially labeled, for example using different fluorescent labels, so as to differentiate between RNA from different target genes.

Multiplex, such as duplex, real-time RT-PCR enables simultaneous quantification of 2 targets in the same reaction, which saves time, reduces costs, and conserves samples. These advantages of multiplex, real-time RT-PCR make the technique well-suited for high-throughput gene expression analysis. Multiplex qPCR assay in a real-time format facilitates quantitative measurements and minimizes the risk of false-negative results. It is essential that multiplex PCR is optimized so that amplicons of all samples are compared insub-plateau phase of PCR. Yun, Z., I. Lewensohn-Fuchs, P. Ljungman, L. Ringholm, J. Jonsson, and J. Albert. 2003. A real-time TaqMan PCR for routine quantitation of cytomegalovirus DNA in crude leukocyte lysates from stem cell transplant patients. J. Virol. Methods 110:73-79. [PubMed]. Yun, Z., I. Lewensohn-Fuchs, P. Ljungman, and A. Vahlne. 2000. Real-time monitoring of cytomegalovirus infections after stem cell transplantation using the TaqMan polymerase chain reaction assays. Transplantation 69:1733-1736. [PubMed]. Simultaneous quantification of up to 2, 3, 4, 5, 6, 7, and 8 or more targets may be useful.

The primers and probes contained within the kit may include those listed in 19, and various subcombinations thereof.

A “control population” refers to a defined group of individuals or a group of individuals with or without colorectal cancer, and may optionally be further identified by, but not limited to geographic, ethnic, race, gender, one or more other conditions or diseases, and/or cultural indices. In most cases a control population may encompass at least 10, 50, 100, 1000, or more individuals.

“Positive control data” encompasses data representing levels of RNA encoded by a target gene of the invention in each of one or more subjects having colorectal cancer of the invention, and encompasses a single data point representing an average level of RNA encoded by a target gene of the invention in a plurality of subjects having colorectal cancer of the invention.

“Negative control data” encompasses data representing levels of RNA encoded by a target gene of the invention in each of one or more subjects not having colorectal cancer of the invention, and encompasses a single data point representing an average level of RNA encoded by a target gene of the invention in a plurality of subjects having colorectal cancer of the invention.

The probability that test data of the invention “corresponds” to positive control data or negative control data of the invention refers to the probability that the test data is more likely to be characteristic of data obtained in subjects having colorectal cancer than in subjects not having any colorectal pathology, or is more likely to be characteristic of data obtained in subjects not having any colorectal pathology than in subjects having colorectal cancer, respectively.

A primer which “selectively hybridizes” to a target polynucleotide is a primer which is capable of hybridizing only, or mostly, with a single target polynucleotide in a mixture of polynucleotides consisting of RNA of human blood, or consisting of DNA complementary to RNA of human blood.

A gene expression profile of the invention for colorectal cancer found in blood at the RNA level of one or more genes comprising, but preferably not limited to, an ANXA3 gene, a CLEC4D gene, an IL2RB gene, an LMNB1 gene, a PRRG4 gene, a TNFAIP6 gene and a VNN1 gene, can be identified or confirmed using many techniques, including but preferably not limited to PCR methods, as for example discussed further in the working examples herein, Nothern analyses and the microarray technique. This gene expression profile can be measured in a bodily sample, such as blood, using microarray technology. In an embodiment of this method, fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from blood. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. For example, with dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93(2):106-149 (1996)). Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.

Other features and advantages of the invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples while indicating preferred embodiments of the invention are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will now be described in relation to the drawings in which:

FIGS. 1A-H are sequence diagrams depicting the nucleotide sequences of the following genes: ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, respectively.

FIG. 2 is a schematic depicting an exemplary computer system for practicing certain of the methods described herein.

DETAILED DESCRIPTION

The invention is of methods, kits, computer systems and computer-readable media for determining a probability that a human subject has colorectal cancer. Specifically, the invention can be used to determine such a probability via analysis of novel markers of colorectal cancer in blood which are disclosed herein.

Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details set forth in the following description or exemplified by the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting.

Effective methods of testing for colorectal cancer via analysis of blood markers would overcome critical disadvantages of prior art methods, which are excessively invasive, cumbersome, risky, unavailable and/or associated with low patient screening compliance rates. While various approaches have been proposed in the prior art for colorectal cancer testing via analysis of markers of this disease in blood (reviewed in Hundt S. et al. Blood markers for early detection of colorectal cancer: a systematic review. Cancer Epidemiol Biomarkers Prey. 2007 October; 16(10): 1935-53), none of these approaches, however, has demonstrated a capacity to satisfactorily enable determination of the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer.

Thus, the prior art fails to provide an effective method of testing a subject for colorectal cancer via analysis in a blood sample of levels of RNA encoded by one or more of the genes ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 blood markers.

While reducing the invention to practice it was surprisingly uncovered that levels of RNA encoded by the genes ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 are significantly higher in blood of subjects having colorectal cancer than in blood of subjects not having any colorectal pathology, and that levels of RNA encoded by IL2RB are significantly lower in blood of subjects having colorectal cancer than in blood of subjects not having any colorectal pathology (Example 2). While further reducing the invention to practice, it was surprisingly uncovered that mathematical models based on levels of RNA encoded by the 127 possible combinations of the colorectal cancer marker genes ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of a test subject could be derived capable of discriminating between subjects having colorectal cancer and subjects not having any colorectal pathology (Example 2). While further reducing the invention to practice, it was surprisingly uncovered that mathematical models based on levels of RNA encoded by the 63 possible combinations of the colorectal cancer marker genes ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6, and VNN1 in blood of a test subject, when normalized against levels of RNA encoded by IL2RB, could be derived capable of discriminating between subjects having colorectal cancer and subjects not having any colorectal pathology (Example 3). It will be appreciated that application of such mathematical models to test data representing blood levels in a test subject of RNA encoded by the aforementioned novel colorectal cancer marker genes disclosed herein can be used to provide the probability that the test subject has colorectal cancer as opposed to not having any colorectal pathology.

While reducing the invention to practice, fold changes of blood levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, including fold-changes of levels normalized to IL2RB, in subjects having colorectal cancer relative to subjects not having any colorectal pathology were surprisingly uncovered (Example 2, Example 3 and Example 6).

Thus, according to one aspect of the invention there is provided a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer. In a first step, the method is effected by determining, for each gene of a set of one or more of the colorectal cancer marker genes: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1; a level of RNA encoded by the gene in blood of the test subject, thereby generating test data. In a second step, the method is effected by determining the probability that the test data corresponds to positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer and not to negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. The probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

Thus, according to an aspect of the invention, there is provided a method of classifying a test subject as being more likely to have colorectal cancer than to not have colorectal cancer. The method of classifying is effected by determining a level of RNA encoded by one or more of the set of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and/or VNN1 in blood of the test subject, to thereby generate test data and applying to the test data, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. For ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer; and where, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

Determining whether the level of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 or VNN1 in blood of the test subject is higher than the level of RNA encoded by the gene in blood of control subjects not having colorectal cancer may be effected by determining whether there is a fold-change in the level between the test subject and the control subjects not having colorectal cancer which is higher than a minimum fold-change and/or which is within a range of fold-changes.

Determining whether the level of RNA encoded by IL2RB in blood of the test subject is lower than the level of RNA encoded by the gene in blood of control subjects not having colorectal cancer may be effected by determining whether there is a fold-change in the level between the test subject and the control subjects not having colorectal cancer which is lower than a maximum fold-change and/or which is within a range of fold-changes.

Examples of suitable fold-changes and ranges of fold-changes for classifying a test subject according to the invention are provided in Example 2, Example 3 and Example 6, below, and include the following ones.

For levels of RNA encoded by ANXA3, a suitable minimum fold-change is about 1.6 fold, and a suitable range of fold-changes is about 1.6 to about 11.5 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by CLEC4D, a suitable minimum fold-change is which is about 1.4 fold, and a suitable range of fold-changes is which is about 1.4 to about 15.9 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by LMNB1, a suitable minimum fold-change is about 1.3 fold, and a suitable range of fold-changes is about 1.3 to about 7.0 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by PRRG4, a suitable minimum fold-change is about 1.5 fold, and a suitable range of fold-changes is about 1.5 to about 6.3 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by TNFAIP6, a suitable minimum fold-change is about 1.4 fold, and a suitable range of fold-changes is about 1.45 to about 16.8 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by VNN1, a suitable minimum fold-change is about 1.5 fold, and a suitable range of fold-changes is about 1.45 to about 23.6 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by IL2RB, a suitable maximum fold-change is about 0.8 fold, and a suitable range of fold-changes is about 0.8 to about 0.1 fold, relative to an average level of RNA encoded by the housekeeping gene in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by ANXA3 normalized to IL2RB, a suitable minimum fold-change is about 1.7 fold, and a suitable range of fold-changes is about 1.7 to about 20.7 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by CLEC4D normalized to IL2RB, a suitable minimum fold-change is which is about 1.5 fold, and a suitable range of fold-changes is which is about 1.5 to about 12.0 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by LMNB1 normalized to IL2RB, a suitable minimum fold-change is about 1.5 fold, and a suitable range of fold-changes is about 1.5 to about 10.6 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by PRRG4 normalized to IL2RB, a suitable minimum fold-change is about 1.3 fold, and a suitable range of fold-changes is about 1.3 to about 13.1 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by TNFAIP6 normalized to IL2RB, a suitable minimum fold-change is about 1.5 fold, and a suitable range of fold-changes is about 1.5 to about 16.4 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

For levels of RNA encoded by VNN1 normalized to IL2RB, a suitable minimum fold-change is about 1.3 fold, and a suitable range of fold-changes is about 1.3 to about 11.9 fold, relative to an average level of RNA encoded by IL2RB in blood of subjects not having any colorectal pathology.

As used herein, the term “about” refers to a variability of plus or minus 10 percent.

Thus, a test subject of the invention is classified as being more likely to have colorectal cancer than to not have colorectal cancer if, for each marker gene of the particular set of marker genes of the invention used to practice the method of classifying of the invention, the fold-change in level of RNA encoded by that gene in blood of the test subject relative to blood of the control subjects not having any colorectal cancer pathology classifies, according to the teachings of the invention, the test subject as being more likely to have colorectal cancer than to not have colorectal cancer.

Conversely, a test subject of the invention is classified as being more likely to not have colorectal cancer than to have colorectal cancer if, for each marker gene of the particular set of marker genes of the invention used to practice the method of classifying of the invention, the fold-change in level of RNA encoded by that gene in blood of the test subject relative to blood of the control subjects not having any colorectal cancer pathology does not classify, according to the teachings of the invention, the test subject as being more likely to have colorectal cancer than to not have colorectal cancer.

In one aspect of the invention, the set of one or more colorectal cancer marker genes may consist of any one of the possible combinations of one or more of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 (indicated in Table 6, where each logistic regression model is based on one particular gene combination, and each gene of the combination is assigned a logistic regression coefficient value).

Sets of marker genes of the invention which consist of one or more of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 which can be used to practice the invention include: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, VNN1; ANXA3, CLEC4D, IL2RB, PRRG4; ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4; ANXA3, CLEC4D, IL2RB, PRRG4, VNN1; ANXA3, IL2RB, LMNB1, PRRG4, VNN1; ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6; ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6; ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6; ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6, VNN1; ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ANXA3, IL2RB, LMNB1, PRRG4; IL2RB, PRRG4, VNN1; ANXA3, IL2RB, PRRG4, VNN1; CLEC4D, IL2RB, PRRG4, VNN1; IL2RB, LMNB1, PRRG4, VNN1; CLEC4D, IL2RB, LMNB1, PRRG4, VNN1; ANXA3, IL2RB, PRRG4, TNFAIP6; IL2RB, PRRG4, TNFAIP6, VNN1; ANXA3, IL2RB, PRRG4, TNFAIP6, VNN1; CLEC4D, IL2RB, PRRG4, TNFAIP6, VNN1; IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; IL2RB, PRRG4; ANXA3, IL2RB, PRRG4; CLEC4D, IL2RB, PRRG4; IL2RB, LMNB1, PRRG4; CLEC4D, IL2RB, LMNB1, PRRG4; IL2RB, PRRG4, TNFAIP6; CLEC4D, IL2RB, PRRG4, TNFAIP6; IL2RB, LMNB1, PRRG4, TNFAIP6; CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6; ANXA3, IL2RB, VNN1; ANXA3, CLEC4D, IL2RB, VNN1; ANXA3, IL2RB, LMNB1, VNN1; ANXA3, CLEC4D, IL2RB, LMNB1, VNN1; ANXA3, CLEC4D, LMNB1, PRRG4, VNN1; ANXA3, IL2RB, TNFAIP6, VNN1; ANXA3, CLEC4D, IL2RB, TNFAIP6, VNN1; ANXA3, IL2RB, LMNB1, TNFAIP6, VNN1; ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6, VNN1; ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1; ANXA3, IL2RB; ANXA3, CLEC4D, IL2RB; ANXA3, IL2RB, LMNB1; ANXA3, CLEC4D, IL2RB, LMNB1; ANXA3, CLEC4D, LMNB1, PRRG4; CLEC4D, IL2RB, LMNB1, VNN1; ANXA3, IL2RB, TNFAIP6; ANXA3, CLEC4D, IL2RB, TNFAIP6; ANXA3, IL2RB, LMNB1, TNFAIP6; ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6; ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6; IL2RB, LMNB1, TNFAIP6, VNN1; CLEC4D, IL2RB, LMNB1, TNFAIP6, VNN1; IL2RB, LMNB1, VNN1; ANXA3, LMNB1, PRRG4, VNN1; ANXA3, LMNB1, PRRG4, TNFAIP6, VNN1; ANXA3, CLEC4D, PRRG4; ANXA3, LMNB1, PRRG4; CLEC4D, IL2RB, VNN1; ANXA3, CLEC4D, PRRG4, VNN1; IL2RB, LMNB1, TNFAIP6; CLEC4D, IL2RB, LMNB1, TNFAIP6; ANXA3, CLEC4D, PRRG4, TNFAIP6; ANXA3, LMNB1, PRRG4, TNFAIP6; IL2RB, TNFAIP6, VNN1; CLEC4D, IL2RB, TNFAIP6, VNN1; ANXA3, CLEC4D, PRRG4, TNFAIP6, VNN1; IL2RB, LMNB1; CLEC4D, IL2RB, LMNB1; IL2RB, VNN1; ANXA3, CLEC4D, LMNB1, VNN1; ANXA3, CLEC4D, LMNB1, TNFAIP6, VNN1; ANXA3, CLEC4D, LMNB1; ANXA3, PRRG4; ANXA3, CLEC4D, VNN1; ANXA3, LMNB1, VNN1; ANXA3, PRRG4, VNN1; ANXA3, CLEC4D, LMNB1, TNFAIP6; ANXA3, PRRG4, TNFAIP6; ANXA3, CLEC4D, TNFAIP6, VNN1; ANXA3, LMNB1, TNFAIP6, VNN1; ANXA3, PRRG4, TNFAIP6, VNN1; ANXA3; ANXA3, CLEC4D; ANXA3, LMNB1; ANXA3, VNN1; ANXA3, TNFAIP6; ANXA3, CLEC4D, TNFAIP6; IL2RB, TNFAIP6; CLEC4D, IL2RB, TNFAIP6; ANXA3, LMNB1, TNFAIP6; ANXA3, TNFAIP6, VNN1; CLEC4D, IL2RB; PRRG4, VNN1; CLEC4D, PRRG4, VNN1; LMNB1, PRRG4, VNN1; CLEC4D, LMNB1, PRRG4, VNN1; PRRG4, TNFAIP6, VNN1; CLEC4D, PRRG4, TNFAIP6, VNN1; LMNB1, PRRG4, TNFAIP6, VNN1; CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1; PRRG4; CLEC4D, PRRG4; LMNB1, PRRG4; CLEC4D, LMNB1, PRRG4; PRRG4, TNFAIP6; CLEC4D, PRRG4, TNFAIP6; LMNB1, PRRG4, TNFAIP6; CLEC4D, LMNB1, PRRG4, TNFAIP6; LMNB1, TNFAIP6, VNN1; CLEC4D, VNN1; LMNB1, VNN1; CLEC4D, LMNB1, VNN1; LMNB1, TNFAIP6; LMNB1, TNFAIP6; TNFAIP6, VNN1; CLEC4D, TNFAIP6, VNN1; CLEC4D, LMNB1, TNFAIP6, VNN1; LMNB1; CLEC4D, LMNB1; VNN1; CLEC4D, TNFAIP6; TNFAIP6; CLEC4D; and IL2RB.

According to the aspect of the invention where the set of one or more colorectal cancer marker genes consists of any one of the 127 possible combinations of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, the level of RNA encoded by a gene of the invention in blood of a subject of the invention may be determined as a ratio to a level of RNA encoded by a housekeeping gene in blood of the subject. It will be appreciated that such measurement of a level or RNA encoded by a gene relative to that of a housekeeping gene within individual samples can be used to control for sample to sample variability.

The housekeeping gene may be any one of various genes expressed in blood known to the ordinarily skilled artisan. In one aspect of the method, the housekeeping gene is ACTB. Alternately, the housekeeping gene may encode 18S rRNA.

Nucleotide sequences of target genes of the invention (ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1) are described in FIGS. 1A-H and in Table 1, below.

In another aspect of the invention, the set of one or more colorectal cancer marker genes may consist of any one of the possible combinations of one or more of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 (indicated in Table 5, where each logistic regression model is based on one particular gene combination, and each gene of the combination is assigned a logistic regression coefficient value).

The possible combinations of one or more of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 which can be used to practice the invention include: ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1; ANXA3, LMNB1, PRRG4, TNFAIP6 and VNN1; ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6; ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1; ANXA3, PRRG4, TNFAIP6 and VNN1; CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1; ANXA3, PRRG4 and TNFAIP6; CLEC4D, LMNB1, PRRG4 and TNFAIP6; ANXA3, CLEC4D, PRRG4, TNFAIP6 and VNN1; ANXA3, CLEC4D, PRRG4 and TNFAIP6; ANXA3, LMNB1, PRRG4 and VNN1; ANXA3, LMNB1, PRRG4 and TNFAIP6; CLEC4D, LMNB1, PRRG4 and VNN1; ANXA3, CLEC4D, LMNB1, PRRG4; ANXA3, CLEC4D, PRRG4 and VNN1; LMNB1, PRRG4 and VNN1; LMNB1, PRRG4, TNFAIP6 and VNN1; LMNB1, PRRG4 and TNFAIP6; ANXA3, CLEC4D and PRRG4; ANXA3, LMNB1 and PRRG4; ANXA3 and PRRG4; ANXA3, PRRG4 and VNN1; CLEC4D, LMNB1 and PRRG4; LMNB1 and PRRG4; CLEC4D, PRRG4, TNFAIP6 and VNN1; CLEC4D, PRRG4 and TNFAIP6; CLEC4D, PRRG4 and VNN1; CLEC4D and PRRG4; PRRG4, TNFAIP6 and VNN1; PRRG4 and VNN1; PRRG4 and TNFAIP6; PRRG4; TNFAIP6 and VNN1; VNN1; ANXA3, TNFAIP6 and VNN1; ANXA3, LMNB1, TNFAIP6 and VNN1; LMNB1, TNFAIP6 and VNN1; CLEC4D, TNFAIP6 and VNN1; ANXA3, CLEC4D, TNFAIP6 and VNN1; ANXA3, CLEC4D, LMNB1, TNFAIP6 and VNN1; CLEC4D, LMNB1, TNFAIP6 and VNN1; ANXA3 and VNN1; ANXA3, CLEC4D, LMNB1 and TNFAIP6; CLEC4D, LMNB1 and TNFAIP6; CLEC4D and VNN1; LMNB1 and VNN1; ANXA3, CLEC4D and VNN1; ANXA3, LMNB1 and VNN1; ANXA3, LMNB1 and TNFAIP6; LMNB1 and TNFAIP6; CLEC4D, LMNB1 and VNN1; ANXA3, CLEC4D, LMNB1 and VNN1; ANXA3, CLEC4D and TNFAIP6; CLEC4D and TNFAIP6; CLEC4D, LMNB1; ANXA3, CLEC4D and LMNB1; LMNB1; ANXA3 and TNFAIP6; ANXA3 and LMNB1; TNFAIP6; ANXA3 and CLEC4D; CLEC4D; and ANXA3.

According to the aspect of the invention where the set of one or more colorectal cancer marker genes consists of any one of the 63 possible combinations of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, the level of RNA encoded by a gene of the invention in blood of a subject of the invention may be determined as a ratio to a level of RNA encoded by IL2RB in blood of the subject.

It will be appreciated that data representing levels of RNA encoded by a set of genes of the invention may be combined with data representing levels of gene products of other genes which are differently expressed in blood in subjects having colorectal cancer relative to subjects not having any colorectal pathology so as to determine a probability that a test subject has colorectal cancer versus not having any colorectal pathology.

In another aspect, the method further comprises determining levels of RNA encoded by the gene in blood of a population of control human subjects having colorectal cancer, and/or in blood of a population of human control subjects not having colorectal cancer, to thereby provide the positive control data and/or the negative control data, respectively. Alternately, it is envisaged that the level of RNA encoded by a gene of the invention in control subjects of the invention could be provided by prior art data corresponding to control data of the invention.

The method of the invention may be practiced using any one of various types of control subjects.

In an aspect of the method of the invention, the control subjects not having colon cancer are subjects having been diagnosed as not having any colorectal pathology as a result of colonoscopic examination. As is described in the Examples section which follows, the method of the invention may be practiced using subjects not having any colorectal pathology as the control subjects not having colorectal cancer.

In an aspect of the method of the invention, the control subjects having colorectal cancer are subjects having been diagnosed as having colorectal cancer as a result of colonoscopic examination. As is described in the Examples section which follows, the method of the invention may be practiced using subjects diagnosed as not having any colorectal pathology as the control subjects not having colorectal cancer.

The method of the invention may furthermore be practiced using any one of various numbers of control subjects. One of ordinary skill in the art will possess the necessary expertise to select a sufficient number of control subjects so as to obtain control data having a desired statistical significance for practicing the method of the invention with a desired level of reliability.

For example, the method of the invention can be practiced using 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 110 or more, 120 or more, 130 or more, 140 or more, 150 or more, 160 or more, 170 or more, 180 or more, 190 or more, or 200 or more of control subjects having colorectal cancer and/or of control subjects not having colorectal cancer.

In one aspect of the invention, the level of RNA encoded by a gene of the invention in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. As is described in the Examples section, below, the method can be practiced where the level of RNA encoded by a gene of the invention in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. Alternately, it is envisaged that the level of a gene of the invention in blood of a test subject of the invention and in blood of control subjects of the invention could be determined using different methods. It will be appreciated that use of the same method to determine the levels of RNA encoded by a gene of the invention in a test subject and in control subjects of the invention can be used to avoid method-to-method calibration to minimize any variability which might arise from use of different methods.

In one aspect of the method, determining of the level of RNA encoded by a gene of the invention in blood of a subject of the invention is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the subject. Alternately, it is envisaged that determining of the level of RNA encoded by the gene in blood of a subject of the invention could be effected by determining the level of RNA encoded by the gene in an in-vivo sample using a suitable method for such a purpose.

In one aspect of the method, the level of RNA encoded by a gene of the invention in blood of a subject of the invention is determined in a sample of RNA isolated from blood of the subject. Alternately, it is envisaged that the level of RNA of a gene of the invention in blood of a subject of the invention could be determined in a sample which includes RNA of blood of the subject but from which RNA has not been isolated therefrom, using a suitable method for such a purpose.

Any one of various methods routinely employed in the art for isolating RNA from blood may be used to isolate RNA from blood of a subject of the invention, so as to enable practicing of the method of the invention.

In one aspect of the method, the level of RNA encoded by a gene of the invention in blood of a subject of the invention is determined in RNA of a sample of whole blood. Any one of various methods routinely employed in the art for isolating RNA from whole blood may be employed for practicing the method.

Alternately, it is envisaged that the level of RNA encoded by a gene of the invention in blood of a subject of the invention could be determined in RNA of a sample of fraction of blood which expresses the gene sufficiently specifically so as to enable the method. Examples of such blood fractions include preparations of isolated types of leukocytes, preparations of isolated peripheral blood mononuclear cells, preparations of isolated granulocytes, preparations of isolated whole leukocytes, preparations of isolated specific types of leukocytes, plasma-depleted blood, preparations of isolated lymphocytes, and the plasma fraction of blood.

In one aspect of the method, isolation of RNA from whole blood of a subject of the invention is effected by using a PAXgene Blood RNA Tube (obtainable from PreAnalytiX) in accordance with the instructions of the PAXgene Blood RNA Kit protocol. As is described in the Examples section below, the method of the invention may be practiced by determining a level of a gene of the invention in RNA isolated from blood from test and control subjects of the invention using PAXgene Blood RNA Tubes.

Determining of a level of RNA encoded by a gene of the invention in a sample of the invention may be effected in any one of various ways routinely practiced in the art.

For example, the level of RNA encoded by a gene of the invention in a sample of the invention may be determined via any one of various methods based on quantitative polynucleotide amplification which are routinely employed in the art for determining a level of RNA encoded by a gene in a sample.

Alternately, the level of RNA encoded by a gene of the invention may be determined via any one of various methods based on quantitative polynucleotide hybridization to an immobilized probe which are routinely employed in the art for determining a level of RNA encoded by a gene in a sample.

In one aspect of the method of the invention, the method based on quantitative polynucleotide amplification used to determine the level of RNA encoded by a gene of the invention is quantitative reverse transcriptase-polymerase chain reaction (PCR) analysis. Any one of various types of quantitative reverse transcriptase-PCR analyses routinely employed in the art to determine the level of RNA encoded by a gene in a sample may be used to practice the invention. For example, any one of various sets of primers may be used to perform quantitative reverse transcriptase-PCR analysis so as to practice the method of the invention.

In one aspect of the method of the invention, the quantitative reverse transcriptase-PCR analysis used to determine the level of RNA encoded by a gene of the invention is quantitative real-time PCR analysis of DNA complementary to RNA encoded by the gene using a labeled probe capable of specifically binding amplification product of DNA complementary to RNA encoded by the gene. For example, quantitative real-time PCR analysis may be performed using a labeled probe which comprises a polynucleotide capable of selectively hybridizing with a sense or antisense strand of amplification product of DNA complementary to RNA encoded by the gene. Labeled probes comprising a polynucleotide having any one of various nucleic acid sequences capable of specifically hybridizing with amplification product of DNA complementary to RNA encoded by the gene may be used to practice the method of the invention.

Quantitative real-time PCR analysis of a level of RNA encoded by a gene of the invention may be performed in any one of various ways routinely employed in the art. In one aspect of the method of the invention, quantitative real-time PCR analysis is performed by analyzing complementary DNA prepared from RNA of blood a subject of the invention, using the QuantiTect™ Probe RT-PCR system (Qiagen, Valencia, Calif.; Product Number 204345), a TaqMan dual labelled probe, and a Real-Time PCR System 7500 instrument (Applied Biosystems). As is described in the Examples section which follows, such quantitative real-time PCR analysis may be used to practice the method of the invention.

As specified above, the level of RNA encoded by a gene of the invention may be determined via a method based on quantitative polynucleotide hybridization to an immobilized probe.

In one aspect, determining of the level of RNA encoded by a gene of the invention via a method based on quantitative polynucleotide hybridization is effected using a microarray, such as an Affymetrix U133Plus 2.0 GeneChip oligonucleotide array (Affymetrix; Santa Clara, Calif.).

As specified above, the level of RNA encoded by a gene of the invention in a sample of the invention may be determined via quantitative reverse transcriptase-PCR analysis using any one of various sets of primers and labeled probes to amplify and quantitate DNA complementary to RNA encoded by a marker gene of the invention produced during such analysis. Examples of suitable primers for use in quantitative reverse transcriptase-PCR analysis of the level of RNA encoded by a target gene of the invention are listed in Table 19. This table further lists examples of suitable polynucleotides comprised in labeled probes for practicing quantitative real-time PCR analysis according to the method of the invention.

TABLE 19 PCR primers and matching polynucleotides of labeled probes for quantitative PCR analysis. Gene encoding Primer/ amplified Assay Nucleic acid sequences of PCR primers and matching polynucleotides probe Amplicon cDNA reagent comprised in labeled probes position size (bp) ACTB 5′ 5′-CACCACACCTTCTACAATGAGCTG-3′ (SEQ ID NO: 1) 259 158 primer 5′-ACAGCCTGGATAGCAACGTACA-3′ (SEQ ID NO: 2) 416 3′ 5′-AACCGCGAGAAGATGACCCAGATCAT-3′ (SEQ ID NO: 3) 343 primer probe 5′ 5′-ACCTTCTACAATGAGCTGCG-3′ (SEQ ID NO: 4) 337 114 primer 5′-GGTCTCAAACATGATCTGGGTC-3′ (SEQ ID NO: 5) 450 3′ 5′-AAGGCCAACCGCGAGAAGAT-3′ (SEQ ID NO: 6) 409 primer probe 5′ 5′-CACCCAGCACAATGAAGATC-3′ (SEQ ID NO: 7) 1034 119 primer 5′-CTGCTTGCTGATCCACATCT-3′ (SEQ ID NO: 8) 1152 3′ 5′-ATCATTGCTCCTCCTGAGCG-3′ (SEQ ID NO: 9) 1057 primer probe ANXA3 5′ 5′-GAAACATCTGGTGACTTCCG-3′ (SEQ ID NO: 10) 748 103 primer 5′-TCTGGGCATCTTGTTTGG-3′ (SEQ ID NO: 11) 850 3′ 5′-TTGACTTTGGCAGATGGCAGA-3′ (SEQ ID NO: 12) 778 primer probe 5′ 5′-GGAACAAACGAAGATGCCTTG-3′ (SEQ ID NO: 13) 628 137 primer 5′-AAGTCACCAGATGTTTCGGA-3′ (SEQ ID NO: 14) 764 3′ 5′-ATCTTAACTACCAGGACAAGCAGGCA-3′ (SEQ ID NO: 15) 655 primer probe 5′ 5′-CTACCAGGACAAGCAGGCAA-3′ (SEQ ID NO: 16) 662 138 primer 5′-TTCTGCCATCTGCCAAAGT-3′ (SEQ ID NO: 17) 799 3′ 5′-TCCGAAACATCTGGTGACTTCC-3′ (SEQ ID NO: 18) 745 primer probe CLEC4D 5′ 5′-CCATTTAACCCACGCAGAG-3′ (SEQ ID NO: 19) 673 101 primer 5′-CAGGCCCATTTATCTTGGTT-3′ (SEQ ID NO: 20) 773 3′ 5′-CTGGCATAAGAATGAACCCGACA-3′ (SEQ ID NO: 21) 696 primer probe 5′ 5′-TCCGAAACATCTGGTGACTTCC-3′ (SEQ ID NO: 22) 406 118 primer 5′-TCCTTTCACTCTCAGCCCAC-3′ (SEQ ID NO: 23) 523 3′ 5′-ATGACCATCAGCACGGAAGC-3′ (SEQ ID NO: 24) 550 primer probe 5′ 5′-GGGCTGAGAGTGAAAGGAAC-3′ (SEQ ID NO: 25) 506 149 primer 5′-CCACTGACCTTTGGCATTC-3′ (SEQ ID NO: 26) 654 3′ 5′-ATGACCATCAGCACGGAAGC-3′ (SEQ ID NO: 27) 550 primer probe IL2RB 5′ 5′-AAATCTCCCAAGCCTCCCA-3′ (SEQ ID NO: 28) 588 127 primer 5′-AGGCAGATCCATTCCTGCT-3′ (SEQ ID NO: 29) 714 3′ 5′-TTGAAAGACACCTGGAGTTCG-3′ (SEQ ID NO: 30) 612 primer probe 5′ 5′-GACCCACAGATGCAACATAAG-3′ (SEQ ID NO: 31) 562 137 primer 5′-GCTTCTGCTTGAGAGTCAGC-3′ (SEQ ID NO: 32) 698 3′ 5′-AAATCTCCCAAGCCTCCCAC-3′ (SEQ ID NO: 33) 588 primer probe 5′ 5′-TGGAGACCCACAGATGCAA-3′ (SEQ ID NO: 34) 558 141 primer 5′-GCTTCTGCTTGAGAGTCAGC-3′ (SEQ ID NO: 35) 698 3′ 5′-AAATCTCCCAAGCCTCCCAC-3′ (SEQ ID NO: 36) 588 primer probe LMNB1 5′ 5′-GGAGTGGTTGTTGAGGAAGAA-3′ (SEQ ID NO: 37) 2051 151 primer 5′-CTGAGAAGGCTCTGCACTGTA-3′ (SEQ ID NO: 38) 2201 3′ 5′-AACCCCAAGAGCATCCAATAG-3′ (SEQ ID NO: 39) 2089 primer probe 5′ 5′-CTGGCGAAGATGTGAAGGT-3′ (SEQ ID NO: 40) 1935 135 primer 5′-CTTCCTCAACAACCACTCCA-3′ (SEQ ID NO: 41) 2069 3′ 5′-AATTCTCAGGGAGAGGAGGTTG-3′ (SEQ ID NO: 42) 1964 primer probe 5′ 5′-AGGCGAAGAAGAGAGGTTGAAG-3′ (SEQ ID NO: 43) 1513 103 primer 5′-CCGCTTTCCTCTAGTTGTACG-3′ (SEQ ID NO: 44) 1615 3′ 5′-TGTCTCCAAGCCCTTCTTCC-3′ (SEQ ID NO: 45) 1536 primer probe PRRG4 5′ 5′-ATGCGGGAGAAGAAGTGTTTAC-3′ (SEQ ID NO: 46) 341 153 primer 5′-CTCTGGCTTCCTCATAATTGC-3′ (SEQ ID NO: 47) 493 3′ 5′-CTCTTCACTCCCGGCAACCTAGAA-3′ (SEQ ID NO: 48) 427 primer probe 5′ 5′-TGCTGCTGGAGTATTTTTGG-3′ (SEQ ID NO: 49) 618 130 primer 5′-AATGATGGAGGGAGTGTGC-3′ (SEQ ID NO: 50) 747 3′ 5′-AACATCCATGCTCTTCAGCC-3′ (SEQ ID NO: 51) 693 primer probe 5′ 5′-ACTCCCGGCAACCTAGAAAG-3′ (SEQ ID NO: 52) 433 176 primer 5′-GTCAGAAGGCCCATAACATCTA-3′ (SEQ ID NO: 53) 608 3′ 5′-AACGATTGCATTTTGGCAGG-3′ (SEQ ID NO: 54) 517 primer probe TNFAIP6 5′ 5′-GCCTATTGCTACAACCCACA-3′ (SEQ ID NO: 55) 448 84 primer 5′-TGGGAAGCCTGGAGATTTA-3′ (SEQ ID NO: 56) 531 3′ 5′-AAGGAGTGTGGTGGCGTCTTTAC-3′ (SEQ ID NO: 57) 472 primer probe 5′ 5′-CAGGTTGCTTGGCTGATTATG-3′ (SEQ ID NO: 58) 632 172 primer 5′-TTGATTTGGAAACCTCCAGC-3′ (SEQ ID NO: 59) 803 3′ 5′-TGGCTTTGTGGGAAGATACTGTGG-3′ (SEQ ID NO: 60) 684 primer probe 5′ 5′-CATTAGACTCAAGTATGGTCAGCG-3′ (SEQ ID NO: 61) 567 142 primer 5′-TCCACAGTATCTTCCCACAAAG-3′ (SEQ ID NO: 62) 708 3′ 5′-CAGGTTGCTTGGCTGATTATGT-3′ (SEQ ID NO: 63) 632 primer probe VNN1 5′ 5′-TGACAGGAAGTGGCATCTAT-3′ (SEQ ID NO: 64) 835 147 primer 5′-TACTGCTGGCATAGGAAGTC-3′ (SEQ ID NO: 65) 981 3′ 5′-AGAAGAGGGAAAACTCCTCCTCTCG-3′ (SEQ ID NO: 66) 896 primer probe 5′ 5′-CTGGAGAATTTCAGGTGTCA-3′ (SEQ ID NO: 67) 1360 111 primer 5′-ATGCCCAGTCCTTCTCATAC-3′ (SEQ ID NO: 68) 1470 3′ 5′-ACTGACGGACGCTTGTTTAGTCTGA-3′ (SEQ ID NO: 69) 1380 primer probe 5′ 5′-GTATTCCCAACAGCTTGGAT-3′ (SEQ ID NO: 70) 711 144 primer 5′-ATAGATGCCACTTCCTGTCA-3′ (SEQ ID NO: 71) 854 3′ 5′-CATGAGGGTCAATTTCCTTGCATC-3′ (SEQ ID NO: 72) 785 primer probe

Determining the level of RNA encoded by the marker gene of the invention as a ratio to a housekeeping gene may be effected in any one of various ways routinely employed in the art for determining a ratio of a level of RNA encoded by one gene to a level of RNA encoded by a housekeeping gene, such as ACTB.

In one aspect of the method, determining the level of RNA encoded by the gene of the invention as a ratio to the housekeeping gene is effected via duplex quantitative reverse transcriptase-PCR analysis of RNA encoded by the gene and of RNA encoded by the housekeeping gene in a sample of the invention. Such “duplex quantitative reverse transcriptase PCR analysis” refers to quantitative reverse transcriptase-PCR analysis where DNA complementary to RNA encoded by the gene of the invention and DNA complementary to RNA encoded by the housekeeping gene are co-amplified in the same sample/reaction mixture.

DNA complementary to RNA encoded by the housekeeping gene may be amplified via quantitative reverse transcriptase-PCR analysis using any one of various suitable primers.

In one aspect, the primers may be selected so as to include a primer having a nucleotide sequence which is complementary to a region of a target cDNA template, where the region spans a splice junction joining a pair of exons. It will be appreciated that such a primer can be used to facilitate amplification of DNA complementary to messenger RNA, i.e. mature spliced RNA.

In one aspect of the method, where the housekeeping gene is ACTB, the primers used to amplify DNA complementary to RNA encoded by the housekeeping gene may include a primer having a nucleotide sequence identified as SEQ ID NO: 1, a primer having a nucleotide sequence identified as SEQ ID NO: 2, or both primers.

In another aspect of the method, the level of RNA encoded by the housekeeping gene in blood of the test subject is determined via quantitative reverse transcriptase-PCR analysis, using a labeled probe which comprises a polynucleotide capable of hybridizing to a sense or antisense strand of the amplification product of the DNA complementary to RNA encoded by the housekeeping gene.

In one aspect of the method where the housekeeping gene is ACTB and where the level of RNA encoded by the housekeeping gene in blood of the test subject is determined via quantitative reverse transcriptase-PCR analysis using a primer having a nucleotide sequence identified as SEQ ID NO: 1, and a primer having a nucleotide sequence identified as SEQ ID NO: 2, and a labeled probe, the probe comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 3.

As is demonstrated in Example 2 of the Examples section which follows, the method of the invention can be practiced by determining the level of RNA encoded by any one of the marker genes ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 as a ratio to a level of RNA encoded by ACTB in blood of a subject of the invention, where the level is determined via duplex quantitative reverse transcriptase-PCR analysis using a primer having a nucleotide sequence identified as SEQ ID NO: 1, a primer having a nucleotide sequence identified as SEQ ID NO: 2, and a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 3.

Determining the level of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 or VNN1 as a ratio to IL2RB may be effected in any one of various ways.

In one aspect of the method, determining the level of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 or VNN1 as a ratio to a level of RNA encoded by IL2RB in a sample of the invention is effected via duplex quantitative reverse transcriptase-PCR analysis of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 or VNN1 and of RNA encoded by IL2RB in the sample. Such “duplex quantitative reverse transcriptase PCR analysis” refers to quantitative reverse transcriptase-PCR analysis where DNA complementary to RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 or VNN1 and DNA complementary to RNA encoded by IL2RB are co-amplified in the same sample/reaction mixture.

As described above, following the step of obtaining the test data, the method of the invention comprises the step of determining the probability that the test data corresponds to the positive control data and not to the negative control data.

It will be appreciated that the probability that the test subject does not have any colorectal pathology as opposed to having colorectal cancer can be readily determined from the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. For example, when expressing the probability that the test subject has colorectal cancer as a percentage probability, the probability that the test subject does not have any colorectal pathology as opposed to having colorectal cancer corresponds to 100 percent minus the probability that the test subject does not have any colorectal pathology as opposed to having colorectal cancer.

Determining the probability that the test data corresponds to the positive control data and not to the negative control data may be effected in any one of various ways known to the ordinarily skilled artisan for determining the probability that a gene expression profile of a test subject corresponds to a gene expression profile of subjects having a pathology and not to a gene expression profile of subjects not having the pathology, where the gene expression profiles of the subjects having the pathology and the subjects not having the pathology are significantly different.

In one aspect of the method, determining the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data.

Various suitable mathematical models which are well known in the art of medical diagnosis using disease markers may be employed to classify a test subject as more likely to have colorectal cancer than to not have colorectal cancer, to determine a probability that a test subject is likely to have colorectal cancer as opposed to not having colorectal cancer, or to diagnose a test subject as having colorectal cancer according to the teachings of the invention. Generally these mathematical models can be unsupervised methods performing a clustering whilst supervised methods are more suited to classification of datasets. (refer, for example, to: Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. J Biomed Inform. 2002 October-December; 35(5-6):352-9; Pepe M S. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford, England: Oxford University Press; 2003; Dupont W D. Statistical Modeling for Biomedical Researchers. Cambridge, England: Cambridge University Press; 2002; Pampel F C. Logistic regression: A Primer. Publication # 07-132, Sage Publications: Thousand Oaks, Calif. 2000; King E N, Ryan T P. A preliminary investigation of maximum likelihood logistic regression versus exact logistic regression. Am Statistician 2002; 56:163-170; Metz C E. Basic principles of ROC analysis. Semin Nucl Med 1978; 8:283-98; Swets J A. Measuring the accuracy of diagnostic systems. Science 1988; 240:1285-93; Zweig M H, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 1993; 39:561-77; Witten I H, Frank Eibe. Data Mining: Practical Machine Learning Tools and Techniques (second edition). Morgan Kaufman 2005; Deutsch J M. Evolutionary algorithms for finding optimal gene sets in microarray prediction. Bioinformatics 2003; 19:45-52; Niels Landwehr, Mark Hall and Eibe Frank (2003) Logistic Model Trees. pp 241-252 in Machine Learning: ECML 2003: 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, Sep. 22-26, 2003, Proceedings Publisher: Springer-Verlag GmbH, ISSN: 0302-9743). Examples of such mathematical models, related to learning machine, include: Random Forests methods, logistic regression methods, neural network methods, k-means methods, principal component analysis methods, nearest neighbour classifier analysis methods, linear discriminant analysis, methods, quadratic discriminant analysis methods, support vector machine methods, decision tree methods, genetic algorithm methods, classifier optimization using bagging methods, classifier optimization using boosting methods, classifier optimization using the Random Subspace methods, projection pursuit methods, genetic programming and weighted voting methods.

In one aspect of the invention, the model used is a logistic regression model. As is described in the Examples section below, logistic regression models, can be used according to the method of the invention to determine the probability a test subject of the invention has colorectal cancer as opposed to not having any colorectal pathology. Logistic regression models may also be referred to in the art as “logistic models”, and “logit models”.

Any one of various particular cases of logistic regression models may be used, for any given set of genes of the invention, for determining the probability that the test data corresponds to the positive control data and not to the negative control data.

In one aspect of the method, determining the probability that the test data corresponds to the positive control data and not to the negative control data is effected by using one or more of the logistic regression models disclosed in Example 2, Example 3 and Example 6.

It will be appreciated that a computer may be used for determining the probability that the test subject has colorectal cancer using a mathematical model, according to the method of the invention.

One of skill in the art will know of suitable mathematical formulas for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher or lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer.

For example, a suitable formula, is one which generates a value representing the ratio of the level of RNA encoded by the gene in blood of the test subject to the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. A ratio of greater than 1 indicates that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and a ratio of less than 1 indicates that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. A formula for generating such a ratio value may have the form:

Value=[level of RNA encoded by the gene in blood of the test subject]/[level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer]

Alternately, a suitable formula is one which subtracts the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer from the level of RNA encoded by the gene in blood of the test subject, to generate a value representing the difference between the level of RNA encoded by the gene in blood of the test subject from the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. A difference having a positive value indicates that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and a difference having a negative value indicates that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. A formula for generating such a difference value may have the form:

Value=[level of RNA encoded by the gene in blood of the test subject]−[level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer]

Thus, according to another aspect of the invention there is provided a computer-based method of determining the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer. The method is effected by causing a computer to apply to the test data a mathematical model according to the invention, and to output the probability, to thereby enable a determination of the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

Application of computers for determining a probability that a test subject has a disease as opposed to not having the disease, so as to enable the method of the invention, is routinely practiced in the art using computer systems, and optionally computer-readable media, routinely used in the art.

Thus, according to a further aspect of the invention there is provided a computer system for providing the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. The computer system comprises a processor; and a memory configured with instructions that cause the processor to provide a user with the probability, where the instructions comprise applying a mathematical model of the invention to test data of the invention, to thereby determine the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

The instructions may be provided to the computer in any one of various ways routinely employed in the art. In one aspect, the instructions are provided to the computer using a computer-readable medium.

Thus, according to yet another aspect of the invention there is provided a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying a mathematical model of the invention to test data of the invention from, thereby determine the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer.

As described above, following the step of obtaining the test data, the method of classifying of the invention comprises the step of comparing test data representing a level of RNA encoded by a marker gene of the invention to negative control data representing a level of RNA encoded by the gene in subjects not having any colorectal pathology, and determining the fold-change between the levels.

It will be appreciated that a computer may be used for comparing test data representing a level of RNA encoded by a marker gene of the invention to negative control data representing a level of RNA encoded by the gene in subjects not having any colorectal pathology, and determining the fold-change between the levels, according to methods of the invention.

Thus, according to another aspect of the invention there is provided a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer. The method is effected by using a computer to apply to test data from a test subject according to the invention, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, or lower, for IL2RB, than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. For ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

Application of computers for provide a classification of a test subject as more likely to have a disease than to not have the disease, so as to enable the method of the invention, is routinely practiced in the art using computer systems, and optionally computer-readable media, routinely used in the art.

Thus, according to a further aspect of the invention there is provided a computer system for providing a classification that a test subject is more likely to have colorectal cancer than to not have colorectal cancer. The computer system comprises a processor; and a memory configured with instructions that cause the processor to provide a user with the classification, where the instructions comprise causing the processor to apply to test data, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value representing a fold-change between the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer where, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, a value indicating that the level of RNA encoded by the gene in blood of the test subject is higher, for example within a range of suitable fold-changes taught herein, than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, a value indicating that the level of RNA encoded by the gene in blood of the test subject is lower, for example within a range of suitable fold-changes disclosed herein, than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

The instructions may be provided to the computer in any one of various ways routinely employed in the art. In one aspect, the instructions are provided to the computer using a computer-readable medium.

Thus, according to yet another aspect of the invention there is provided a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying to test data and to negative control data representing a level of RNA encoded by a marker gene of the invention in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value representing the fold-change between the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, a value indicating that the level of RNA encoded by the gene in blood of the test subject is higher, for example, within a suitable range of fold-changes disclosed herein, than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, a value indicating that the level of RNA encoded by the gene in blood of the test subject is lower, for example, within a suitable range of fold-changes disclosed herein, than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

Thus, according to still yet another aspect of the invention there is provided a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying, to test data representing a level of RNA encoded by the gene in blood of a human test subject, and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

An exemplary computer system for practicing certain of the methods described herein is described in FIG. 1.

FIG. 1 shows a schematic of a general-purpose computer system 100 suitable for practicing the methods described herein. The computer system 100, shown as a self-contained unit but not necessarily so limited, comprises at least one data processing unit (CPU) 102, a memory 104, which will typically include both high speed random access memory as well as non-volatile memory (such as one or more magnetic disk drives) but may be simply flash memory, a user interface 108, optionally a disk 110 controlled by a disk controller 112, and at least one optional network or other communication interface card 114 for communicating with other computers as well as other devices. At least the CPU 102, memory 104, user interface 108, disk controller where present, and network interface card, communicate with one another via at least one communication bus 106.

Memory 104 stores procedures and data, typically including: an operating system 140 for providing basic system services; application programs 152 such as user level programs for viewing and manipulating data, evaluating formulae for the purpose of diagnosing a test subject; authoring tools for assisting with the writing of computer programs; a file system 142, a user interface controller 144 for handling communications with a user via user interface 108, and optionally one or more databases 146 for storing data of the invention and other information, optionally a graphics controller 148 for controlling display of data, and optionally a floating point coprocessor 150 dedicated to carrying out mathematical operations. The methods of the invention may also draw upon functions contained in one or more dynamically linked libraries, not shown in FIG. 1, but stored either in Memory 104, or on disk 110, or accessible via network interface connection 114.

User interface 108 may comprise a display 128, a mouse 126, and a keyboard 130. Although shown as separate components in FIG. 1, one or more of these user interface components can be integrated with one another in embodiments such as handheld computers. Display 128 may be a cathode ray tube (CRT), or flat-screen display such as an LCD based on active matrix or TFT embodiments, or may be an electroluminescent display, based on light emitting organic molecules such as conjugated small molecules or polymers. Other embodiments of a user interface not shown in FIG. 1 include, e.g., several buttons on a keypad, a card-reader, a touch-screen with or without a dedicated touching device, a trackpad, a trackball, or a microphone used in conjunction with voice-recognition software, or any combination thereof, or a security-device such as a fingerprint sensor or a retinal scanner that prohibits an unauthorized user from accessing data and programs stored in system 100.

System 100 may also be connected to an output device such as a printer (not shown), either directly through a dedicated printer cable connected to a serial or USB port, or wirelessly, or via a network connection.

The database 146 may instead, optionally, be stored on disk 110 in circumstances where the amount of data in the database is too great to be efficiently stored in memory 104. The database may also instead, or in part, be stored on one or more remote computers that communicate with computer system 100 through network interface connection 114.

The network interface 134 may be a connection to the interne or to a local area network via a cable and modem, or ethernet, firewire, or USB connectivity, or a digital subscriber line. Preferably the computer network connection is wireless, e.g., utilizing CDMA, GSM, or GPRS, or bluetooth, or standards such as 802.11a, 802.11b, or 802.11g.

It would be understood that various embodiments and configurations and distributions of the components of system 10 across different devices and locations are consistent with practice of the methods described herein. For example, a user may use a handheld embodiment that accepts data from a test subject, and transmits that data across a network connection to another device or location where the data is analyzed according to a formulae described herein. A result of such an analysis can be stored at the other location and/or additionally transmitted back to the handheld embodiment. In such a configuration, the act of accepting data from a test subject can include the act of a user inputting the information. The network connection can include a web-based interface to a remote site at, for example, a healthcare provider. Alternatively, system 10 can be a device such as a handheld device that accepts data from the test subject, analyzes the data, such as by inputting the data into a formula as further described herein, and generating a result that is displayed to the user. The result can then be, optionally, transmitted back to a remote location via a network interface such as a wireless interface. System 100 may further be configured to permit a user to transmit by e-mail results of an analysis directly to some other party, such as a healthcare provider, or a diagnostic facility, or a patient.

In one aspect of the invention there is provided a method of determining whether a subject is at an increased risk of having colorectal cancer relative to the general population. The method comprises obtaining a test biological sample of blood from the subject; for each of a set of genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, determining the amount of RNA encoded by the gene in the test biological sample; comparing the determined amount of RNA for each these genes with the amount in one or more control biological samples of blood; and concluding or determining that the subject is at increased risk, average risk or decreased risk of having colorectal cancer relative to the general population if the amount of RNA encoded by each gene in the test biological sample is higher than in the control biological samples for genes ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and lower for IL2RB.

A test subject would be considered as being at “increased risk” of having or developing colorectal cancer if the amount of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and/or VNN1 present in the test biological sample is higher than that seen in the control samples to an approximate extent (plus or minus 10%) seen in the working examples herein. A test subject would be considered as being at “increased risk” of having or developing colorectal cancer if the amount of RNA encoded by IL2RB present in the test biological sample is lower than that seen in the control samples to an approximate extent (plus or minus 10%) seen in the working examples herein.

A combination of marker genes of the invention, such as ANXA3, CLEC4D, LMNB1, PRRG4, VNN1, and IL2RB, can be used together with the known CRC prevalence rate to determine useful thresholds for stratifying the probability of having colorectal cancer in an average risk population. Using the combined training/blind set (IL2RB duplex) described in the Examples, an increased probability threshold can be selected to identify a sub-population with a colorectal cancer occurrence rate of 1.5%, a 3-fold increase over the base disease prevalence rate; this threshold reflects the same relative risk associated with having a first degree relative with colorectal cancer. A decreased probability threshold reflecting a sensitivity for colorectal cancer detection of, for example, 80%, 75%, 70%, 65%, can be selected to identify a lower-than-average probability sub-population. This approach can be used to stratify patients into an increased probability group, a decreased probability, and an average probability group.

One of ordinary skill in the art will be able to determine directly from the literature, or will be able to calculate from available statistical data, a suitable prevalence rate of colorectal cancer for practicing embodiments of the invention. For example, the prevalence rate for colorectal cancer in the average risk population over 50 years of age has been determined to be 0.7% (see for example Imperiale T F. et al., 2004. Colorectal Cancer Study Group. Fecal DNA versus fecal occult blood for colorectal-cancer screening in an average-risk population. New Engl J Med 351:2704-14).

It will be appreciated that components for practicing quantitative PCR according to the method of the invention may be assembled in a kit.

Thus, according to still another aspect of the invention there is provided a kit. The kit comprises packaging and contains, for each gene of a set of two or more of the following target genes of the invention: ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1; a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.

In various aspects of the kit of the invention, the set of genes may be any combination of two or more of the target genes of the invention, as described hereinabove and in the Examples section, below.

In one aspect of the invention, the kit further contains two or more of the following components: a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer.

In another aspect of the invention, the kit further contains at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.

In yet another aspect of the invention, the kit further contains a computer-readable medium of the invention.

In one aspect, the kit is identified in print in or on the packaging as being for determining a probability that a test subject has colorectal cancer, for example, a probability that a test subject has colorectal cancer as opposed to not having colorectal cancer.

In another aspect, the kit is identified in print in or on the packaging as being for classifying a test subject as being more likely to have colorectal cancer than to not have colorectal cancer, and/or as being more likely to not have colorectal cancer than to have colorectal cancer.

In a further aspect, the kit is identified in print in or on the packaging as being for determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population

In various aspects of the kit of the invention, the set of genes may be any combination of two or more of the target genes of the invention.

Sets of genes of the invention which consist of two or more of ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 include: ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, PRRG4; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4; ACTB, ANXA3, CLEC4D, IL2RB, PRRG4, VNN1; ACTB, ANXA3, IL2RB, LMNB1, PRRG4, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6; ACTB, ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6; ACTB, ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, IL2RB, LMNB1, PRRG4; ACTB, IL2RB, PRRG4, VNN1; ACTB, ANXA3, IL2RB, PRRG4, VNN1; ACTB, CLEC4D, IL2RB, PRRG4, VNN1; ACTB, IL2RB, LMNB1, PRRG4, VNN1; ACTB, CLEC4D, IL2RB, LMNB1, PRRG4, VNN1; ACTB, ANXA3, IL2RB, PRRG4, TNFAIP6; ACTB, IL2RB, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, IL2RB, PRRG4, TNFAIP6, VNN1; ACTB, CLEC4D, IL2RB, PRRG4, TNFAIP6, VNN1; ACTB, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, IL2RB, PRRG4; ACTB, ANXA3, IL2RB, PRRG4; ACTB, CLEC4D, IL2RB, PRRG4; ACTB, IL2RB, LMNB1, PRRG4; ACTB, CLEC4D, IL2RB, LMNB1, PRRG4; ACTB, IL2RB, PRRG4, TNFAIP6; ACTB, CLEC4D, IL2RB, PRRG4, TNFAIP6; ACTB, IL2RB, LMNB1, PRRG4, TNFAIP6; ACTB, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6; ACTB, ANXA3, IL2RB, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, VNN1; ACTB, ANXA3, IL2RB, LMNB1, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, VNN1; ACTB, ANXA3, CLEC4D, LMNB1, PRRG4, VNN1; ACTB, ANXA3, IL2RB, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, TNFAIP6, VNN1; ACTB, ANXA3, IL2RB, LMNB1, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, IL2RB; ACTB, ANXA3, CLEC4D, IL2RB; ACTB, ANXA3, IL2RB, LMNB1; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1; ACTB, ANXA3, CLEC4D, LMNB1, PRRG4; ACTB, CLEC4D, IL2RB, LMNB1, VNN1; ACTB, ANXA3, IL2RB, TNFAIP6; ACTB, ANXA3, CLEC4D, IL2RB, TNFAIP6; ACTB, ANXA3, IL2RB, LMNB1, TNFAIP6; ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6; ACTB, ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6; ACTB, IL2RB, LMNB1, TNFAIP6, VNN1; ACTB, CLEC4D, IL2RB, LMNB1, TNFAIP6, VNN1; ACTB, IL2RB, LMNB1, VNN1; ACTB, ANXA3, LMNB1, PRRG4, VNN1; ACTB, ANXA3, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, PRRG4; ACTB, ANXA3, LMNB1, PRRG4; ACTB, CLEC4D, IL2RB, VNN1; ACTB, ANXA3, CLEC4D, PRRG4, VNN1; ACTB, IL2RB, LMNB1, TNFAIP6; ACTB, CLEC4D, IL2RB, LMNB1, TNFAIP6; ACTB, ANXA3, CLEC4D, PRRG4, TNFAIP6; ACTB, ANXA3, LMNB1, PRRG4, TNFAIP6; ACTB, IL2RB, TNFAIP6, VNN1; ACTB, CLEC4D, IL2RB, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, PRRG4, TNFAIP6, VNN1; ACTB, IL2RB, LMNB1; ACTB, CLEC4D, IL2RB, LMNB1; ACTB, IL2RB, VNN1; ACTB, ANXA3, CLEC4D, LMNB1, VNN1; ACTB, ANXA3, CLEC4D, LMNB1, TNFAIP6, VNN1; ACTB, ANXA3, CLEC4D, LMNB1; ACTB, ANXA3, PRRG4; ACTB, ANXA3, CLEC4D, VNN1; ACTB, ANXA3, LMNB1, VNN1; ACTB, ANXA3, PRRG4, VNN1; ACTB, ANXA3, CLEC4D, LMNB1, TNFAIP6; ACTB, ANXA3, PRRG4, TNFAIP6; ACTB, ANXA3, CLEC4D, TNFAIP6, VNN1; ACTB, ANXA3, LMNB1, TNFAIP6, VNN1; ACTB, ANXA3, PRRG4, TNFAIP6, VNN1; ACTB, ANXA3; ACTB, ANXA3, CLEC4D; ACTB, ANXA3, LMNB1; ACTB, ANXA3, VNN1; ACTB, ANXA3, TNFAIP6; ACTB, ANXA3, CLEC4D, TNFAIP6; ACTB, IL2RB, TNFAIP6; ACTB, CLEC4D, IL2RB, TNFAIP6; ACTB, ANXA3, LMNB1, TNFAIP6; ACTB, ANXA3, TNFAIP6, VNN1; ACTB, CLEC4D, IL2RB; ACTB, PRRG4, VNN1; ACTB, CLEC4D, PRRG4, VNN1; ACTB, LMNB1, PRRG4, VNN1; ACTB, CLEC4D, LMNB1, PRRG4, VNN1; ACTB, PRRG4, TNFAIP6, VNN1; ACTB, CLEC4D, PRRG4, TNFAIP6, VNN1; ACTB, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1; ACTB, PRRG4; ACTB, CLEC4D, PRRG4; ACTB, LMNB1, PRRG4; ACTB, CLEC4D, LMNB1, PRRG4; ACTB, PRRG4, TNFAIP6; ACTB, CLEC4D, PRRG4, TNFAIP6; ACTB, LMNB1, PRRG4, TNFAIP6; ACTB, CLEC4D, LMNB1, PRRG4, TNFAIP6; ACTB, LMNB1, TNFAIP6, VNN1; ACTB, CLEC4D, VNN1; ACTB, LMNB1, VNN1; ACTB, CLEC4D, LMNB1, VNN1; ACTB, LMNB1, TNFAIP6; ACTB, LMNB1, TNFAIP6; ACTB, TNFAIP6, VNN1; ACTB, CLEC4D, TNFAIP6, VNN1, ACTB, CLEC4D, LMNB1, TNFAIP6, VNN1; ACTB, LMNB1; ACTB, CLEC4D, LMNB1; ACTB, VNN1; ACTB, CLEC4D, TNFAIP6; ACTB, TNFAIP6; ACTB, CLEC4D; and ACTB, IL2RB.

In one aspect of the kit of the invention, the set of one or more genes consists of a housekeeping gene such as ACTB, and one or more of the colorectal cancer marker genes: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and ANXA3.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and CLEC4D.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and IL2RB.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and LMNB1.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and PRRG4.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and TNFAIP6.

In one aspect of the kit of the invention, the set of one or more genes consists of ACTB and VNN1.

In another aspect of the kit of the invention, the set of one or more genes consists of IL2RB, and one or more of the colorectal cancer marker genes: ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 .

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and ANXA3.

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and CLEC4D.

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and LMNB1.

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and PRRG4.

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and TNFAIP6.

In one aspect of the kit of the invention, the set of one or more genes consists of IL2RB and VNN1.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 1, and a primer having a nucleotide sequence identified as SEQ ID NO: 2.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 1, and a primer having a nucleotide sequence identified as SEQ ID NO: 2 and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 3.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 10, and a primer having a nucleotide sequence identified as SEQ ID NO: 11.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 10, and a primer having a nucleotide sequence identified as SEQ ID NO: 11, and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 12.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 19, and a primer having a nucleotide sequence identified as SEQ ID NO: 20.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 19, and a primer having a nucleotide sequence identified as SEQ ID NO: 20 and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 21.

In one aspect of the invention, for example, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 28, and a primer having a nucleotide sequence identified as SEQ ID NO: 29.

In one aspect of the invention, for example, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 28, and a primer having a nucleotide sequence identified as SEQ ID NO: 29 and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 30.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 37, and a primer having a nucleotide sequence identified as SEQ ID NO: 38.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 37, and a primer having a nucleotide sequence identified as SEQ ID NO: 38 and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 39.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 46, and a primer having a nucleotide sequence identified as SEQ ID NO: 47.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 46, and a primer having a nucleotide sequence identified as SEQ ID NO: 47, and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 48.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 55, and a primer having a nucleotide sequence identified as SEQ ID NO: 56.

In one aspect of the invention, the kit contains a primer having a nucleotide sequence identified as SEQ ID NO: 55, and a primer having a nucleotide sequence identified as SEQ ID NO: 56 and the kit further contains a labeled probe which comprises a polynucleotide having a nucleic acid sequence identified as SEQ ID NO: 57.

Further, non-limiting, specific aspects of the invention include the following:

One aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising: the steps of (a) determining a level of RNA encoded by a ANXA3 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of (a) determining a level of RNA encoded by a CLEC4D gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of (a) determining a level of RNA encoded by a IL2RB gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of: (a) determining a level of RNA encoded by a LMNB1 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of: (a) determining a level of RNA encoded by a PRRG4 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of: (a) determining a level of RNA encoded by a TNFAIP6 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising the steps of: (a) determining a level of RNA encoded by a VNN1 gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

An embodiment of aspects of the invention disclosed herein includes that the determining of the level of RNA encoded by the gene in blood of the test subject be effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject. An embodiment of aspects of the invention disclosed herein includes the further step of determining the levels of RNA encoded by the gene in blood of a population of human subjects having colorectal cancer, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. An embodiment of aspects of the invention disclosed herein includes that the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of aspects of the invention disclosed herein includes that the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of aspects of the invention disclosed herein includes that the determining of the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data, and where the mathematical model is for determining the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data. An embodiment of aspects of the invention disclosed herein includes that the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. An aspect of this latter embodiment includes that the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of aspects of the invention disclosed herein includes that the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. An aspect of this latter embodiment includes that the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

An aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: inputting, to a computer, test data representing a level of RNA encoded by a CLEC4D gene in blood of the test subject; and causing the computer to apply to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: inputting, to a computer, test data representing a level of RNA encoded by a IL2RB gene in blood of the test subject; and causing the computer to apply to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject, the method comprising computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.

An embodiment of the invention's computer based methods includes where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of computer based methods of the invention includes where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of each of computer based methods of the invention includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. An embodiment of computer based methods of the invention includes where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of each of the computer based methods of the invention includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. In a further embodiment the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

Another aspect of the invention disclosed herein is a method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: comprising the steps of: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. An embodiment of this aspect of the invention disclosed herein is where the determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject. An embodiment of this aspect of the invention disclosed herein further comprises determining levels of RNA encoded by the gene in blood of a population of human subjects having colorectal cancer, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. An embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of this aspect of the invention disclosed herein is where the determining of the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data, and where the mathematical model is for determining the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data. An embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. In a further embodiment, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. In a further embodiment, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

Another aspect of the invention disclosed herein is a computer-based method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, from test data representing a level of RNA encoded by the gene in blood of the test subject, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, computer-implemented steps of: (a) applying to the test data a mathematical model derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data; and (b) outputting the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. In an embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. In an embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. In an embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. In a further embodiment of this aspect of the invention disclosed herein is where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. In an embodiment of this aspect of the invention disclosed herein is where the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. In a further embodiment of this aspect of the invention disclosed herein, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB. In an embodiment of this aspect of the invention disclosed herein is where the set of one or more genes consists of PRRG4. In an embodiment of this aspect of the invention disclosed herein is where the set of one or more genes consists of IL2RB and PRRG4.

Another aspect of the invention disclosed herein is a kit comprising packaging and containing, for each gene of a set of two or more genes selected from the group consisting of ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene. An embodiment of this aspect of the invention disclosed herein is where the kit further contains two or more components selected from the group consisting of a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer. An embodiment of this aspect of the invention disclosed herein is where the kit further contains at least one labelled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product. An embodiment of this aspect of the invention disclosed herein is where the kit further contains a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying a mathematical model to test data representing a level of RNA encoded by the gene in blood of a human test subject, where the mathematical model is derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, and where the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of the kit consists of ACTB and one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and ANXA3. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and CLEC4D. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and IL2RB. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and LMNB1. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and PRRG4. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and TNFAIP6. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of ACTB and VNN1. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and ANXA3. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of \ IL2RB and CLEC4D. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and LMNB1. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and PRRG4. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and TNFAIP6. An embodiment of this aspect of the invention disclosed herein is where the set of one or more genes of one or more genes of the kit consists of IL2RB and VNN1.

Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a ANXA3 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a CLEC4D gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a IL2RB gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a LMNB1 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a PRRG4 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a TNFAIP6 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising: (a) determining a level of RNA encoded by a VNN1 gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

An embodiment of the methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer of the invention includes determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject. An embodiment of the invention's methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer of the invention includes further determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. An embodiment of the invention's methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer of the invention includes where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of the invention's methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer of the invention includes where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of the invention's methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer of the invention includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. In an aspect of this embodiment, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of the invention's methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject, and/or where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a ANXA3 gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a CLEC4D gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a IL2RB gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a LMNB1 gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a PRRG4 gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a TNFAIP6 gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by a VNN1 gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (b) outputting the value, where an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.

An embodiment of the invention's computer-based methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, includes where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of the invention's computer-based methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, includes where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of the invention's computer-based methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. An aspect of this embodiment includes where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of the invention's computer-based methods of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. An aspect of this embodiment includes where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

Another aspect of the invention disclosed herein is a method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. An embodiment of this aspect includes determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject. Another embodiment of this aspect includes further comprising determining levels of RNA encoded by the gene in blood of a population of human subjects having colorectal cancer, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer. Another embodiment of this aspect includes where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. An embodiment of this aspect includes where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. An embodiment of this aspect includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. An further embodiment includes where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. An embodiment of this aspect includes where the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. An embodiment of this aspect includes where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB.

Another aspect of the invention disclosed herein is a computer-based method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, computer-implemented steps of: (a) applying to test data representing a level of RNA encoded by the gene in blood of the test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a formula for calculating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and indicating, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, where, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and where, for IL2RB, an indication that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer. An embodiment of this aspect of the invention disclosed herein includes where the level of RNA encoded by the gene in blood of the test subject is determined via quantitative reverse transcriptase-polymerase chain reaction analysis. Another embodiment of this aspect of the invention disclosed herein includes where the level of RNA encoded by the gene in blood of the test subject and the levels of RNA encoded by the gene in blood of the control subjects are determined via the same method. Another embodiment of this aspect of the invention disclosed herein includes where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by ACTB in blood of the test subject. In a further embodiment of this embodiment of the invention as disclosed herein is where the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by ACTB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by ACTB. Another embodiment of this aspect of the invention disclosed herein includes where the set of one or more genes is a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, and where the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. In a further embodiment of this embodiment of the invention as disclosed herein, the level of RNA encoded by the gene in blood of the test subject and the level of RNA encoded by IL2RB in blood of the test subject are determined via duplex quantitative reverse transcriptase-polymerase chain reaction analysis of RNA encoded by the gene and of RNA encoded by IL2RB. In a further embodiment of this embodiment of the invention as disclosed herein, the set of one or more genes consists of PRRG4. In a further embodiment of this embodiment of the invention as disclosed herein, the set of one or more genes consists of IL2RB and PRRG4.

Another aspect of the invention disclosed herein is a kit comprising packaging and containing, for each gene of a set of two or more genes selected from the group consisting of ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, Only by the gene. In an embodiment of this aspect of the invention disclosed herein, the kit further containing two or more components selected from the group consisting of a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer. In another embodiment of this aspect of the invention disclosed herein, the kit further contains at least one labelled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and ANXA3. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and CLEC4D. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and IL2RB. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and LMNB1. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and PRRG4. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and TNFAIP6. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of ACTB and VNN1. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and one or more genes selected from the group consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists IL2RB and ANXA3. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and CLEC4D. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and LMNB1. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and PRRG4. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and TNFAIP6. In another embodiment of this aspect of the invention disclosed herein, the set of one or more genes of the kit consists of IL2RB and VNN1.

Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a annexin A3 (ANXA3) gene in the test sample of blood, (ii) comparing the level of RNA encoded by ANXA3 as determined in step (i) with a level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a C-type lectin domain family 4, member D (CLEC4D) gene in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a interleukin 2 receptor, beta (IL2RB) gene in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a lamin B1 (LMNB1) gene in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a proline rich Gla (G carboxyglutamic acid) 4 (transmembrane) (PRRG4) gene in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a tumor necrosis factor, alpha induced protein 6 gene (TNFAIP6) in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and (i) determining a level of RNA encoded by a vanin 1 (VNN1) gene in the test sample of blood, (ii) comparing the level of RNA encoded by the gene as determined in step (i) with the level of the RNA encoded by the gene in control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood. In an embodiment of any one of these eight aspects these methods of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, the control samples are from individuals who have been diagnosed as not having colorectal cancer.

Another aspect of the invention disclosed herein is a method of determining whether a test subject is at an increased risk of having colorectal cancer relative to the general population, comprising: (a) obtaining a test sample of blood from the subject; and for each gene of a set of genes selected from the group consisting of: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, (i) determining a level of RNA encoded by the gene in the test sample of blood, thereby generating test data; and (ii) applying to the test data and to control data representing a level of RNA encoded by the gene in one or more control samples of blood a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood, and, for IL2RB, whether the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood; and (b) concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, the value indicates that the level of RNA encoded by the gene in the test sample of blood is higher than in the control samples of blood, and concluding that the subject is at an increased risk of having colorectal cancer relative to the general population if, for IL2RB, the value indicates that the level of RNA encoded by the gene in the test sample of blood is lower than in the control samples of blood. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by an ANXA3 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a CLEC4D gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a IL2RB gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a LMNB1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a PRRG4 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a TNFAIP6 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, and VNN1, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a VNN1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, and TNFAIP6, cDNA complementary to the RNA of the group of genes, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes.

Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an ANXA3 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an CLEC4D gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an IL2RB gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an LMNB1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, PRRG4, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a PRRG4, gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, TNFAIP6 and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. Another aspect of the invention disclosed herein is an isolated composition comprising an isolated nucleic acid molecule of a blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a TNFAIP6 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, and VNN1, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes. An isolated composition comprising a blood sample from a test subject and a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by a VNN1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. One embodiment of this composition further comprises a nucleic acid molecule selected from one or more of the group consisting of RNA encoded by one or more genes selected from the group of genes consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, and TNFAIP6, cDNA complementary to the RNA of the group of genes or the complement thereof, an oligonucleotide which specifically hybridizes to the cDNA complementary to the RNA of the group of genes or to the RNA of the group of genes under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA of the group of genes, and an amplification product of the cDNA of the RNA of the group of genes.

Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a LMNB1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an ANXA3 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a CLEC4D gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a LMNB1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an CLEC4D gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a LMNB1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an IL2RB gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a LMNB1 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a LMNB1 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by an LMNB1 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a PRRG4 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof. Another aspect of the invention disclosed herein is a primer set comprising a first primer, where the first primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a VNN1 gene, and a second primer, where the second primer is one of a set of primers capable of generating an amplification product of cDNA complementary to RNA of encoded by a TNFAIP6 gene, or composition thereof.

Another aspect of the invention disclosed herein is test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an ANXA3 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a CLEC4D, gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an IL2RB gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by an LMNB1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a PRRG4 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a TNFAIP6 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. Another aspect of the invention disclosed herein is a test system comprising: a) two or more blood samples where each blood sample is from a different test subject, and b) an isolated nucleic acid molecule of each the blood sample from a test subject, where the nucleic acid molecule is selected from one or more of the group consisting of RNA encoded by a VNN1 gene, cDNA complementary to the RNA, an oligonucleotide which specifically hybridizes to the cDNA or complement thereof, or the RNA under stringent conditions, a primer set capable of generating an amplification product of the cDNA complementary to RNA, and an amplification product of the cDNA. An embodiment of any of the test systems described in this paragraph includes where the test subject is being screened for colorectal cancer.

The following non-limiting examples are illustrative of the invention:

EXAMPLES Example 1 General Materials and Methods

Introduction: The following materials and methods describe experiments performed to demonstrate that analysis of blood for levels of RNA encoded by genes surprisingly identified by the present inventors as colorectal cancer marker genes in blood via array hybridization analysis using an Affymetrix U133Plus 2.0 GeneChip oligonucleotide array (Affymetrix; Santa Clara, Calif.) (data not shown), can also serve as blood markers for diagnosing colorectal cancer via quantitative reverse-transcriptase PCR analysis.

Blood sample collection: Samples of 2.5 ml whole blood were collected into PAXgene Blood RNA Tubes (PreAnalytiX) from human subjects not having any colorectal pathology and from human subjects having colorectal cancer. Samples were obtained from subjects enrolled in colorectal cancer studies conducted by GeneNews Corp. and collaborating institutions. Blood samples from subjects having colorectal cancer were collected prior to tumor resection, and cancer stage and histology were determined by institutional pathologists. Blood samples from subjects not having any colorectal pathology were collected from subjects presenting for endoscopy screening. Informed consent was obtained according to the research protocols approved by the research ethical boards of the institutions involved. Experimental group sample pairs were selected with an effort to match gender, age, body mass index (BMI), ethnicity and medical history. Samples were divided into training and test sets.

RNA isolation: A sample of 2.5 ml whole blood was collected into PAXgene Blood RNA tubes (PreAnalytiX) and processed in accordance with the instructions of the PAXgene Blood RNA Kit protocol. In brief, after storing the blood in the PAXgene tube for at least 2 hours, the blood sample was centrifuged and the supernatant discarded. To the remaining sample, 350 microliters of the supplied Buffer BR1 was added, and the sample was pipetted into the spin column and centrifuged, washed and finally eluted as isolated RNA and stored.

Reverse transcription: Reverse transcription of blood sample-derived RNA into single-stranded complementary DNA was performed using the High Capacity cDNA Reverse Transcription Kit from (Applied Biosystems; Foster City, Calif.; Product number 4368814), according to the manufacturer's instructions. Specifically, 1 microgram of isolated RNA was incubated with reverse transcriptase buffer, dNTPs, random primers and reverse transcriptase and incubated at 25° C. for 10 minutes and subsequently at 37° C. for two hours.

Quantitative real time RT-PCR: Quantitative real-time PCR analysis to measure levels of RNA encoded by the genes listed in Table 1 was performed on cDNA samples using the QuantiTect™ Probe RT-PCR system (Qiagen; Valencia, Calif.; Product No. 204345), using the primers listed in Table 2 for amplification of cDNA template corresponding to the indicated gene, and TaqMan dual labelled probes comprising the polynucleotides listed in Table 3 for measuring levels of amplicon corresponding to the indicated gene. The TaqMan probe and primers were ordered from Applied Biosystems Assays-On-Demand, or from IDT (Integrated DNA Technologies, Coralville, Iowa), or from Biosearch Technologies (Novato, Calif.). XXX SPECIFY PROBES USED IN EXAMPLES & PEAmplicon levels were measured in real time using a Real-Time PCR System 7500 instrument (Applied Biosystems). Specifically, 20 nanograms of cDNA resulting from reverse transcription was added to the QuantiTect Probe PCR Master Mix as provided and no adjustments were made for magnesium concentration. Uracil-N-Glycosylase was not added. Both forward primer and reverse primer (Table 1) specific to the target genes were added to a concentration of 5 micromolar, and the resultant 25 microliter reaction volume was incubated as follows: 50 degrees centigrade for 2 minutes, followed by 95 degrees centigrade for 15 minutes, followed by 40 cycles of: [94 degrees centigrade for 15 seconds, followed by 55 degrees centigrade for 35 seconds, followed by 72 degrees centigrade for 30 seconds]. Amplification data was collected during each of the 40 incubations at 55 degrees centigrade. All quantitative reverse transcriptase-PCR analyses were performed as duplex amplifications of a target gene and a reference gene (either ACTB or IL2RB, as indicated) in the same reaction mixture. Serial dilution measurements for target and duplex partner genes were assayed, to ensure that the values were within linear range and that the amplification efficiencies were approximately equal. Examination via polyacrylamide gel electrophoresis provided confirmation of specific PCR amplification and the lack of primer-dimer formation in each reaction well.

TABLE 1 Genes encoding target RNAs for determining colorectal cancer probability versus absence of colorectal pathology. Gene Symbol GenBank Accession Gene Description ACTB NM_001101 beta-actin ANXA3 NM_005139 annexin A3 CLEC4D NM_080387 C-type lectin domain family 4, member D IL2RB NM_000878 interleukin 2 receptor, beta LMNB1 NM_005573 lamin B1 PRRG4 NM_024081 proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) TNFAIP6 NM_007115 tumor necrosis factor, alpha-induced protein 6 VNN1 NM_004666 vanin 1

TABLE 2 Primers used for quantitative PCR analysis. Gene encoding amplified Primer Amplicon cDNA Primer Primer pair sequences position size (bp) ACTB 5′ 5′-CACCACACCTTCTACAATGAGCTG-3′ (SEQ ID NO: 1) 259 158 3′ 5′-ACAGCCTGGATAGCAACGTACA-3′ (SEQ ID NO: 2) 416 ANXA3 5′ 5′-GAAACATCTGGTGACTTCCG-3′ (SEQ ID NO: 10) 748 103 3′ 5′-TCTGGGCATCTTGTTTGG-3′ (SEQ ID NO: 11) 850 CLEC4D 5′ 5′-CCATTTAACCCACGCAGAG-3′ (SEQ ID NO: 19) 673 101 3′ 5′-CAGGCCCATTTATCTTGGTT-3′ (SEQ ID NO: 20) 773 IL2RB 5′ 5′-AAATCTCCCAAGCCTCCCA-3′ (SEQ ID NO: 28) 588 127 3′ 5′-AGGCAGATCCATTCCTGCT-3′ (SEQ ID NO: 29) 714 LMNB1 5′ 5′-GGAGTGGTTGTTGAGGAAGAA-3′ (SEQ ID NO: 37) 2051 151 3′ 5′-CTGAGAAGGCTCTGCACTGTA-3′ (SEQ ID NO: 38) 2201 PRRG4 5′ 5′-ATGCGGGAGAAGAAGTGTTTAC-3′ (SEQ ID NO: 46) 341 153 3′ 5′-CTCTGGCTTCCTCATAATTGC-3′ (SEQ ID NO: 47) 493 TNFAIP6 5′ 5′-GCCTATTGCTACAACCCACA-3′ (SEQ ID NO: 55) 448 84 3′ 5′-TGGGAAGCCTGGAGATTTA-3′ (SEQ ID NO: 56) 531 VNN1 5′ 5′-TGACAGGAAGTGGCATCTAT-3′ (SEQ ID NO: 64) 835 147 3′ 5′-TACTGCTGGCATAGGAAGTC-3′ (SEQ ID NO: 65) 981

TABLE 3 TaqMan ® probes used for quantitative PCR analysis. Gene encoding Probe amplicon Taqman probe base sequence position ACTB 5′-AACCGCGAGAAGATGACCCAGATCAT-3′ (SEQ ID NO: 3) 343 ANXA3 5′-TTGACTTTGGCAGATGGCAGA-3′ (SEQ ID NO: 12) 778 CLEC4D 5′-CTGGCATAAGAATGAACCCGACA-3′ (SEQ ID NO: 21) 696 IL2RB 5′-TTGAAAGACACCTGGAGTTCG-3′ (SEQ ID NO: 30) 612 LMNB1 5′-AACCCCAAGAGCATCCAATAG-3′ (SEQ ID NO: 39) 2089 PRRG4 5′-CTCTTCACTCCCGGCAACCTAGAA-3′ (SEQ ID NO: 48) 427 TNFAIP6 5′-AAGGAGTGTGGTGGCGTCTTTAC-3′ (SEQ ID NO: 57) 472 VNN1 5′-AGAAGAGGGAAAACTCCTCCTCTCG-3′ (SEQ ID NO: 66) 896

Determination of observed range of fold-changes in levels of RNA encoded by marker genes in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology: For each of the sample training and sample test sets, average fold-change in levels of RNA encoded by marker genes, normalized to either ACTB or IL2RB, were calculated as the ratio of average levels of RNA encoded by marker genes in blood of subjects having colorectal cancer to average levels of RNA encoded by marker genes in blood of subjects not having any colorectal pathology. The statistical significance of the fold-changes were confirmed by a p-value of less than 0.05. Maximum observed directional fold-changes in normalized levels of RNA encoded by marker genes found to be higher in blood of subjects having colorectal cancer than in blood of subjects not having any colorectal pathology were further calculated, for each marker gene, as the ratio of the highest level observed in any single sample from a subject having colorectal cancer to the average level in subjects not having any colorectal pathology. Similarly, maximum observed directional fold-changes in normalized levels of RNA encoded by marker genes found to be lower in blood of subjects having colorectal cancer than in blood of subjects not having any colorectal pathology were further calculated, for each marker gene, as the ratio of the lowest level observed in any single sample from a subject having colorectal cancer to the average level in subjects not having any colorectal pathology. In this way, observed ranges of fold-changes, ranging from average fold-change to maximal observed directional fold-change, in levels of RNA encoded by marker genes in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology were determined.

Formulation of mathematical models for determining probability of colorectal cancer versus absence of colorectal pathology: Logistic regression was used to formulate mathematical models for determining the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology. Levels of RNA encoded by colorectal cancer marker genes and of reference genes determined via duplex quantitative reverse transcriptase PCR in blood of positive and negative control subjects were analyzed via logistic regression so as to generate models having the general form:

P={1+ê−[K ₀ +K ₁ L ₁ +K ₂ L ₂ +K ₃ L ₃ . . . +K _(n) L _(n)]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology; K₀ is a constant; K₁ is a coefficient specific to a first marker gene; L₁ is a ratio of a level of RNA encoded by the first gene to a level of RNA encoded by a reference gene in blood of the test subject; K₂ is a coefficient specific to a second marker gene; L₂ is a ratio of a level of RNA encoded by the second gene to a level of RNA encoded by the reference gene in blood of the test subject; K₃ is a coefficient specific to a third marker gene; L₃ is a ratio of a level of RNA encoded by the third gene to a level of RNA encoded by the reference gene in blood of the test subject; K_(n) is a coefficient specific to an nth marker gene; and L_(n) is a ratio of a level of RNA encoded by the nth gene to a level of RNA encoded by the reference gene in blood of the test subject. The ratio of the level of RNA encoded by a marker gene to the level of RNA encoded by a reference gene was calculated as the change (ΔCt) in the cycle number (Ct) at which the increase in fluorescence is exponential between the marker gene and the reference gene according to the equation: ΔCt=Ct (marker gene)−Ct (reference gene). The caret symbol “̂” is used herein to denote that a value preceding the caret is raised to a power corresponding to the value following the caret.

Example 2 Measurement of Blood Levels of RNA Encoded by any Combination of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and/or VNN1 can be Used to Determine a Probability that a Test Subject has Colorectal Cancer as Opposed to not Having any Colorectal Pathology

Materials and Methods:

Refer to “General materials and methods”, above.

Experimental Results:

Sample Training Set:

Discovery of significantly different levels of RNA encoded by ANXA3, CLEC4D,

IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 and in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology: Quantitative reverse transcriptase PCR analysis of gene expression in a training set of blood samples from 117 subjects having colorectal cancer and 130 subjects not having any colorectal pathology, using the housekeeping gene ACTB as duplex partner for normalization of gene expression levels was performed. The normalized RNA levels measured are shown in Table 4.

TABLE 4 Sample training set levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by ACTB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D IL2RB LMNB1 PRRG4 TNFAIP6 VNN1 CD0011pax 0 6.523 7.755 5.195 7.310 7.860 8.501 8.991 CD0012pax 0 7.878 8.595 5.250 7.525 8.183 8.439 9.878 CD0030pax 0 6.411 6.420 4.173 6.220 6.973 5.901 7.101 CD0063pax 0 7.103 8.545 4.203 7.165 7.795 8.499 8.628 CD0077pax 0 4.808 6.185 5.098 5.405 6.710 6.524 6.533 CD0078pax 0 5.946 7.000 3.553 5.820 5.570 7.476 6.488 CD0085pax 0 5.543 7.700 5.003 6.210 7.460 8.149 6.678 CD0117pax 0 6.021 8.170 4.463 5.685 8.020 8.166 6.573 CD0146pax 0 5.396 6.335 4.468 5.320 5.735 6.691 6.253 CD0167pax 0 3.501 4.893 4.480 4.978 5.590 6.469 5.173 CD0249pax 0 4.443 4.855 4.878 4.803 6.043 5.556 6.471 CD0279pax 0 5.503 7.095 4.270 5.395 6.098 6.694 7.043 CD0286pax 0 4.791 6.928 4.350 5.383 5.960 5.714 5.598 CD0297pax 0 5.861 6.670 5.083 6.565 6.405 6.186 7.118 CD0323pax 0 6.966 7.773 4.645 5.723 7.470 8.149 8.738 CD0445pax 0 6.458 7.420 4.448 6.103 6.448 7.216 7.411 CD0463pax 0 4.391 6.485 4.203 5.605 6.583 6.161 7.036 CD0491pax 0 5.093 6.370 4.928 6.123 6.978 7.171 6.511 CD0496pax 0 6.058 8.270 4.670 6.355 7.783 6.434 6.623 CD0501pax 0 6.326 7.725 4.613 6.270 7.215 8.581 6.978 CD0504pax 0 4.023 5.060 4.858 5.920 7.530 5.289 6.113 CD0573pax 0 6.791 6.140 4.248 6.160 6.713 7.646 7.286 CD0578pax 0 6.328 6.670 4.128 5.128 6.033 6.411 7.081 CD0620pax 0 2.361 3.628 6.120 3.873 6.120 5.274 5.613 CD0639pax 0 5.611 7.013 4.980 6.258 5.630 6.689 7.528 CD0645pax 0 4.596 5.868 5.190 4.908 5.475 6.099 5.608 CD0679pax 0 5.611 7.808 5.070 5.633 6.150 7.974 7.748 CD0685pax 0 5.796 8.150 4.358 6.050 7.155 7.606 6.673 CD0716pax 0 6.961 8.193 4.090 5.648 5.750 6.669 7.388 CD0749pax 0 5.208 6.970 4.520 5.565 6.430 7.176 6.316 CD0760pax 0 2.868 5.020 5.603 3.605 5.790 4.679 5.663 CD0811pax 0 7.188 8.065 3.275 6.500 7.305 6.021 6.141 CD0846pax 0 4.626 6.488 4.730 5.308 5.645 4.864 7.813 CD0848pax 0 5.113 6.235 3.380 5.915 6.388 6.409 7.263 CD0924pax 0 5.731 6.370 5.238 6.095 6.248 5.791 6.131 CD1066pax 0 5.346 5.900 4.903 5.990 6.868 7.466 6.211 CD1073pax 0 5.681 5.813 5.150 5.858 6.350 6.674 6.663 CD1075pax 0 5.128 7.010 4.535 6.075 8.228 7.264 6.563 CD1089pax 0 5.081 7.225 5.733 5.550 6.395 6.546 6.668 CD1116pax 0 4.188 5.500 5.023 5.295 6.180 5.764 6.378 CD1120pax 0 3.663 5.495 5.203 4.780 6.555 6.864 5.118 CD1198pax 0 5.398 6.210 4.155 6.055 6.095 6.086 5.881 PB1179pax 0 6.401 7.293 4.700 6.563 7.080 8.169 7.418 PB1277pax 0 6.403 7.520 4.860 6.260 7.185 7.586 6.351 PB1301pax 0 4.733 6.200 6.268 5.608 6.863 5.891 5.531 PB1315pax 0 3.898 6.165 5.438 4.998 6.008 5.206 7.161 PB1345pax 0 5.246 6.280 4.598 6.410 6.775 6.051 7.663 PB1518pax 0 6.806 7.803 5.055 5.818 7.230 7.134 7.328 PB1520pax 0 4.283 5.560 3.250 4.660 3.793 5.214 6.108 PB1574pax 0 7.538 8.685 5.583 7.453 7.483 7.166 8.226 PB1783pax 0 8.056 9.095 5.453 7.650 8.535 9.011 8.448 PB1799pax 0 7.338 8.760 5.765 7.435 8.855 9.181 7.801 PB1811pax 0 6.848 8.115 5.080 7.140 8.390 7.416 7.471 PB1830pax 0 5.788 7.385 5.923 6.440 6.870 7.444 9.253 PB1833pax 0 5.943 7.620 5.488 6.615 7.620 6.829 8.098 PB1843pax 0 7.218 7.870 5.780 6.770 8.338 5.739 8.708 PB1851pax 0 7.468 8.045 6.050 7.795 8.325 10.181 9.261 PB1919pax 0 8.271 9.525 5.233 7.165 8.975 9.051 9.108 PB1922pax 0 6.788 8.280 6.028 7.363 8.348 9.281 8.306 PB1924pax 0 7.748 8.655 6.758 7.628 8.303 8.816 9.401 PB1937pax 0 7.178 9.085 5.118 7.665 9.740 8.754 8.798 PB1964pax 0 5.491 7.820 4.463 6.065 7.843 7.726 8.496 PB2027pax 0 5.463 6.525 5.150 6.300 7.360 7.401 7.546 PB2029pax 0 5.793 7.060 5.050 6.375 6.973 7.624 7.758 PB2073pax 0 6.021 6.335 4.873 6.290 7.933 6.991 6.846 PB2086pax 0 5.048 5.665 4.208 5.098 6.453 5.286 5.991 PB2099pax 0 4.808 5.360 5.388 5.910 6.680 5.604 7.003 PB2100pax 0 6.353 6.960 4.465 6.085 7.625 7.351 6.826 PB2132pax 0 5.693 7.235 4.438 5.745 6.995 7.649 7.518 PB2168pax 0 6.776 7.593 4.605 6.168 7.125 8.284 6.993 PB2192pax 0 6.701 7.845 5.483 6.230 6.965 7.751 8.378 PB2196pax 0 6.061 7.655 4.573 6.195 7.985 7.781 6.668 PB2200pax 0 6.706 7.640 5.158 6.025 7.103 6.826 6.276 PB2213pax 0 6.898 7.435 4.773 6.380 6.630 8.614 7.448 PB2224pax 0 4.841 5.385 4.743 5.210 6.448 7.546 6.851 PB2228pax 0 6.511 6.915 3.953 6.450 7.373 8.906 8.086 PB2229pax 0 5.771 6.440 5.588 6.030 5.865 7.091 6.528 PB2277pax 0 6.348 6.685 4.290 5.705 5.930 5.986 7.351 PB2297pax 0 5.886 6.785 4.703 5.835 6.533 6.451 5.696 PB2312pax 0 5.533 6.530 3.773 6.098 5.978 6.651 6.746 PB2398pax 0 4.711 5.390 5.033 5.440 5.748 5.136 7.111 PB2409pax 0 5.946 7.195 4.933 5.835 6.950 6.811 7.683 PB2414pax 0 7.843 7.790 3.955 6.380 7.745 9.026 7.101 PB2467pax 0 5.773 6.935 4.260 5.955 6.525 7.596 6.756 PB2473pax 0 6.818 8.275 5.530 7.375 8.405 7.586 8.561 PB2512pax 0 5.603 7.355 4.340 6.215 6.345 6.926 7.511 PB2568pax 0 5.326 5.850 5.303 5.710 7.178 7.561 7.331 PB2571pax 0 5.561 5.995 4.523 6.060 6.173 7.396 7.791 PB2603pax 0 5.778 6.480 3.953 5.903 6.313 7.021 5.986 PB2624pax 0 5.383 5.465 3.948 5.498 6.838 6.146 6.741 PB2824pax 0 5.781 6.748 4.675 5.758 6.830 7.154 7.223 PB2880pax 0 5.906 6.090 4.728 6.160 5.218 7.361 7.386 PB3088pax 0 6.601 6.760 3.858 5.725 6.395 8.456 7.378 RC0882pax 0 5.043 6.540 4.533 5.708 6.083 7.351 7.151 RC0888pax 0 4.726 5.740 4.948 5.330 6.775 6.516 6.168 RC0968pax 0 3.238 3.590 4.008 4.303 6.118 4.716 7.086 RC2114pax 0 4.473 5.900 4.768 5.168 6.028 5.216 7.446 RC2238pax 0 7.318 8.785 5.878 7.175 8.665 9.209 9.903 RC2681pax 0 6.331 7.515 5.623 6.995 7.833 6.471 7.536 RC2703pax 0 8.093 8.360 5.973 7.053 8.253 7.801 8.091 RC2749pax 0 6.448 8.695 5.895 7.205 7.905 7.726 8.666 RC2750pax 0 5.578 6.650 6.753 6.428 7.993 7.761 7.111 RG2756pax 0 7.478 8.135 5.340 7.095 8.420 7.781 8.671 RC2771pax 0 5.848 8.345 6.240 6.440 7.648 8.449 9.303 RC2790pax 0 8.086 9.228 6.880 7.573 8.475 8.679 8.948 RC2792pax 0 7.956 8.058 5.850 7.068 8.320 9.219 8.448 RC2808pax 0 6.556 8.790 5.233 6.605 7.815 7.096 7.653 RC2822pax 0 7.921 9.163 6.255 7.193 8.075 10.284 7.718 RC2834pax 0 6.588 8.535 6.520 6.810 7.920 9.946 9.651 RC2871pax 0 5.443 6.530 4.563 6.280 7.165 7.479 8.158 RC2879pax 0 6.266 8.105 5.978 6.620 8.465 7.971 7.298 RC2892pax 0 6.086 7.423 5.185 6.163 7.185 8.559 7.748 RC2895pax 0 6.148 6.900 4.378 6.270 7.450 6.109 7.473 RC2921pax 0 6.846 7.623 4.720 6.758 7.520 7.954 8.073 RC2958pax 0 6.581 6.735 4.863 6.185 6.638 5.851 7.616 RC3022pax 0 6.401 6.660 4.888 6.685 7.925 7.776 6.578 RC3112pax 0 6.938 8.095 5.408 6.435 7.475 8.629 7.713 RC3146pax 0 6.018 6.655 5.340 5.905 6.855 7.491 7.451 RC3184pax 0 6.998 7.910 4.398 6.370 7.395 7.329 7.598 RC3232pax 0 5.021 6.460 5.003 5.030 7.008 4.941 8.671 RC3324pax 0 5.158 6.220 5.203 5.055 6.935 6.869 5.713 RC3327pax 0 5.238 5.225 4.708 5.313 5.253 6.381 7.541 RC3334pax 0 5.953 7.670 4.710 6.135 6.850 6.816 8.081 RC3355pax 0 5.871 7.253 5.620 5.358 6.325 7.699 6.648 RC3380pax 0 5.418 6.395 5.363 5.453 6.423 6.786 6.481 RC3392pax 0 6.378 8.025 4.445 6.170 7.265 8.546 7.756 RC3413pax 0 6.176 7.940 4.768 6.100 6.545 7.051 8.858 RC3421pax 0 5.661 5.515 5.088 5.900 6.483 5.191 5.961 RC3468pax 0 5.831 5.890 5.443 5.905 6.523 7.171 6.636 RC3498pax 0 5.553 5.515 5.593 6.145 7.200 7.484 6.468 CD0157pax 1 6.223 6.530 4.198 6.115 6.930 7.654 8.168 CD0164pax 1 4.726 5.395 4.083 5.660 10.733 7.791 6.696 CD0256pax 1 4.833 6.295 4.735 6.045 6.785 7.141 6.911 CD0322pax 1 5.153 7.050 6.308 5.820 7.325 7.239 8.603 CD0356pax 1 5.243 5.555 6.038 5.925 6.580 6.239 5.823 CD0371pax 1 5.643 7.110 5.073 6.045 6.245 6.394 5.968 CD0629pax 1 4.453 5.995 4.503 5.555 7.380 5.114 6.563 CD1050pax 1 6.238 5.930 4.943 6.150 7.105 6.969 7.243 MH0001pax 1 7.266 8.375 5.103 7.770 8.568 9.266 8.706 MH0009pax 1 6.078 7.150 5.990 6.325 7.185 6.131 6.426 MH0011pax 1 2.393 4.420 8.808 4.258 6.888 3.846 5.756 MH0012pax 1 4.673 6.965 5.368 5.970 7.680 6.659 7.043 MH0014pax 1 6.266 8.155 5.003 6.395 6.995 9.436 7.983 MH0016pax 1 5.408 6.770 6.225 6.050 6.635 6.181 6.561 MH0017pax 1 6.071 8.290 5.323 6.710 6.750 8.231 8.433 MH0018pax 1 6.856 7.175 5.093 6.250 7.358 8.451 6.791 MH0021pax 1 6.948 6.675 5.263 5.483 6.398 8.236 8.111 MH0022pax 1 6.471 7.508 5.280 6.228 7.030 7.344 7.548 MH0024pax 1 5.016 5.640 4.488 5.340 5.793 5.211 6.241 MH0026pax 1 4.351 6.775 5.558 5.440 6.840 5.861 6.028 MH0028pax 1 6.183 6.815 5.818 5.918 5.883 5.986 6.176 MH0029pax 1 5.388 6.360 5.015 6.255 5.925 6.846 6.831 MH0035pax 1 6.111 8.575 4.708 6.645 7.460 7.051 7.638 MH0037pax 1 5.441 7.063 5.375 5.578 6.325 7.089 7.948 MH0038pax 1 7.206 7.463 5.020 6.748 7.635 8.089 8.113 MH0039pax 1 4.036 5.113 5.110 5.298 5.110 5.394 6.383 MH0042pax 1 4.643 5.560 4.425 5.900 5.785 4.876 5.901 MH0050pax 1 3.763 6.495 4.908 4.718 5.698 6.641 7.721 MH0051pax 1 4.941 5.693 6.225 5.818 4.795 4.044 6.338 PB1829pax 1 7.363 9.380 6.678 7.073 7.428 8.841 9.241 PB1842pax 1 7.483 8.295 6.188 7.488 7.173 8.786 8.011 PB1872pax 1 7.051 8.525 6.318 7.410 7.175 8.486 7.533 PB2857pax 1 4.268 6.600 4.810 5.300 6.470 5.266 6.976 RC2919pax 1 7.106 7.488 4.420 6.463 8.350 8.399 9.318 RC3062pax 1 5.006 6.200 4.513 5.195 6.340 5.271 5.538 RC3277pax 1 5.068 6.360 4.770 5.360 6.205 5.701 6.136 RC3297pax 1 5.748 6.970 4.728 5.843 6.493 8.451 7.206 RC3445pax 1 5.503 6.560 5.290 6.295 6.560 6.711 7.021 RC3467pax 1 6.893 8.640 3.945 6.670 7.040 8.251 7.771 CC0003pax 1 4.281 5.963 5.500 4.608 5.205 7.009 4.853 DC0001pax 1 5.713 5.580 5.378 5.868 6.408 6.201 6.541 DC0002pax 1 6.323 6.125 5.423 6.380 6.410 7.374 7.273 DS0003pax 1 4.816 6.663 6.615 5.248 7.380 6.849 6.398 FC0005pax 1 5.953 6.735 5.618 6.605 6.980 6.649 8.698 FC0011pax 1 6.458 7.550 7.063 6.915 7.950 8.539 8.338 FC0012pax 1 3.868 6.850 7.138 5.285 6.375 6.849 7.063 JGA0001pax 1 5.426 6.250 7.448 6.125 8.173 6.586 7.096 JGA0008pax 1 5.448 7.600 6.018 6.793 7.403 7.366 7.841 JH0002pax 1 6.108 7.335 5.633 6.725 6.950 7.484 7.128 JH0003pax 1 6.053 6.635 5.090 5.905 6.145 5.701 7.081 JH0004pax 1 5.373 5.985 5.265 5.935 6.570 7.371 6.961 JH0005pax 1 5.341 6.565 5.008 5.780 6.688 7.356 7.091 JH0006pax 1 4.771 5.840 5.073 5.525 6.198 6.731 5.551 JH0007pax 1 2.956 3.035 5.353 4.815 6.483 5.661 4.916 JH0008pax 1 5.876 8.435 5.173 6.265 7.573 7.811 6.711 JH0009pax 1 4.101 3.770 4.793 5.540 5.293 4.636 5.876 JH0010pax 1 5.026 5.810 4.958 6.105 7.018 6.046 5.526 JH0012pax 1 4.981 5.435 4.718 5.965 6.318 5.801 6.511 JH0013pax 1 5.501 6.610 5.268 5.905 7.048 8.861 7.191 JH0014pax 1 5.053 5.235 4.253 4.735 4.860 6.259 7.488 JH0016pax 1 5.596 6.390 4.438 5.980 6.338 5.566 6.191 JH0018pax 1 4.401 5.770 5.248 5.765 6.348 5.696 6.446 JH0019pax 1 5.751 6.775 5.468 6.055 6.693 5.926 6.656 JH0020pax 1 5.001 7.450 4.563 5.875 5.618 5.756 6.706 JH0021pax 1 5.726 7.650 6.058 5.730 6.105 6.611 6.808 JH0023pax 1 4.696 6.805 3.873 5.020 6.960 5.951 6.968 JH0024pax 1 6.008 7.895 5.113 6.865 7.620 9.099 8.698 JH0025pax 1 4.796 5.780 5.398 5.150 5.225 5.626 6.423 JH0026pax 1 4.491 6.940 5.363 5.800 6.725 7.646 7.493 JH0027pax 1 3.111 4.720 6.498 4.280 5.225 4.486 5.288 JH0028pax 1 4.416 5.680 3.858 5.395 5.820 7.196 6.378 JH0029pax 1 4.176 5.950 5.063 5.055 5.850 4.971 6.963 JH0031pax 1 5.371 7.385 5.613 6.040 6.595 7.096 7.213 JH0032pax 1 7.326 8.430 4.933 6.075 6.925 8.231 8.408 JH0033pax 1 5.258 8.160 5.380 5.560 6.455 8.126 6.181 JH0034pax 1 4.061 6.560 4.468 5.725 6.135 6.721 6.703 JH0035pax 1 4.051 6.625 3.703 4.690 4.400 6.551 5.523 JH0036pax 1 5.348 6.260 4.608 5.480 6.030 6.904 6.618 JH0038pax 1 4.538 6.195 4.878 5.025 5.945 7.049 5.673 JH0039pax 1 5.458 6.595 4.165 5.525 6.950 8.691 5.141 JH0040pax 1 5.458 6.555 4.773 6.140 6.580 6.144 6.658 JH0041pax 1 6.038 7.940 5.033 6.335 6.760 7.489 7.178 JH0042pax 1 3.191 4.985 5.398 4.500 5.978 4.401 4.221 JH0043pax 1 5.263 6.670 6.073 6.110 5.955 5.779 9.668 JH0046pax 1 5.161 5.360 4.448 5.885 5.808 5.951 5.811 JH0047pax 1 4.396 6.385 4.078 5.625 6.828 6.501 6.836 JH0051pax 1 4.881 6.370 5.158 5.290 5.130 5.676 5.388 JH0052pax 1 5.066 7.240 5.528 5.510 5.625 5.616 5.703 JH0053pax 1 4.653 6.375 5.483 5.258 6.578 5.701 6.571 JH0057pax 1 4.201 7.330 4.208 4.755 6.140 6.661 5.968 JH0059pax 1 3.698 4.950 4.243 4.478 4.668 4.896 5.166 JH0060pax 1 4.733 6.230 5.303 5.833 6.448 6.646 6.861 JH0061pax 1 5.063 7.300 4.298 5.063 6.208 8.041 5.466 JH0063pax 1 4.923 6.845 4.748 5.433 5.178 6.021 7.756 JH0065pax 1 3.263 5.220 5.660 4.510 5.355 4.816 4.301 JH0066pax 1 5.703 7.575 6.638 5.988 5.818 5.851 6.791 JH0068pax 1 5.536 6.448 4.895 5.473 5.925 7.239 7.708 JH0069pax 1 3.723 5.435 4.460 4.800 4.955 4.436 4.061 JH0071pax 1 3.748 4.580 6.050 4.785 5.850 5.096 6.261 JH0072pax 1 5.863 6.185 5.185 6.015 6.035 7.306 6.386 JH0077pax 1 4.473 5.810 5.193 5.635 6.020 5.959 7.278 JH0078pax 1 5.591 5.693 3.685 5.818 4.875 5.419 5.778 JH0080pax 1 2.903 4.470 5.033 4.158 5.093 3.921 6.031 JH0082pax 1 4.611 5.398 4.800 5.108 5.465 5.364 6.683 JH0083pax 1 3.903 6.445 5.398 5.333 4.473 6.006 6.606 JH0086pax 1 5.633 5.850 5.063 5.288 4.978 5.936 7.021 JH0092pax 1 5.241 8.328 5.350 6.113 6.540 6.349 7.663 MIP0004pax 1 3.201 3.098 5.340 3.873 4.510 4.459 2.743 MP0013Apax 1 7.028 9.300 6.195 7.105 8.385 8.561 7.406 MP0014Bpax 1 6.418 8.420 6.623 6.633 8.008 8.746 7.586 MP0018Apax 1 6.003 7.900 7.005 6.740 6.635 7.146 6.281 MP0019Bpax 1 6.283 7.090 6.653 6.528 7.058 6.696 8.656 MP0024pax 1 5.436 7.823 6.375 6.383 7.655 8.939 8.013 NK2001pax 1 5.061 6.843 6.230 5.613 4.680 6.349 7.873 NK2002pax 1 5.516 5.903 5.210 5.568 5.585 6.809 6.753 NK2003pax 1 4.986 6.388 5.590 5.588 6.345 7.404 5.723 NK2004pax 1 4.626 6.648 5.435 5.048 4.945 6.319 5.318

Surprisingly, analysis of the data showed that RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 is present on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology, and that RNA encoded by IL2RB is present on average at a significantly lower level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 5). The ranges of fold-change in the levels of RNA encoded by these genes normalized to levels of RNA encoded by ACTB in blood of the training set subjects having colorectal cancer relative to the training set subjects not having any colorectal pathology are shown in Table 5.

TABLE 5 Sample training set ranges of fold-changes in levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by ACTB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D IL2RB LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized RNA 5.21 6.58 5.28 5.76 6.41 6.64 6.77 level in subjects having colorectal cancer (ΔCt) Average normalized RNA 5.92 7.02 4.95 6.09 7.00 17.19 7.31 level in subjects not having any colorectal pathology (ΔCt) Average RNA level fold- 1.63 1.36 0.80 1.26 1.51 1.46 1.45 change p-value for average RNA level 5.0E−07 2.6E−03 1.1E−03 5.4E−04 2.3E−06 7.0E−04 1.4E−04 fold-change Maximum observed RNA 11.53 15.86 0.07 4.66 6.07 10.12 23.63 level directional fold-change

As can be seen in Table 5, a test subject having a blood level of RNA encoded by ANXA3 which is 1.6 to 11.5 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by CLEC4D which is 1.4 to 15.9 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by LMNB1 which is 1.3 to 4.7 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by PRRG4 which is 1.5 to 6.1 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by TNFAIP6 which is 1.46 to 10.12 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by VNN1 which is 1.45 to 23.63 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 5, a test subject having a blood level of RNA encoded by IL2RB which is 0.8 to 0.1 fold that of the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Generation of logistic regression models for determining the probability that a test subject has colorectal cancer versus not having any colorectal pathology via measurement of levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by ACTB: Linear regression analysis of levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 surprisingly showed that logistic regression models based on blood expression levels of all 127 possible combinations of one or more of these genes determined in the sample training set could be generated, for discriminating, with a receiver-operating characteristic (ROC) area under the curve (AUC) of at least 0.61, between subjects having colorectal cancer and subjects not having any colorectal pathology. Examples of these logistic regression models are shown in Table 6. A model based on ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 (Table 6, Model #1) was surprisingly found to enable discrimination with a ROC AUC of 0.79 between subjects having colorectal cancer and subjects not having any colorectal pathology.

By way of example, Model # 1 of Table 6 corresponds to:

P={1+ê−[0.684+(−0.916)(L _(AXXA3))+(0.353)(L _(CLEC4D))+(0.871)(L _(IL2RB))+(0.907)(L _(LMNB1))+(−0.968)(L _(PRRG4))+(0.154)(L _(TNFAIP6))+(−0.355)(L _(VNN1))]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, L_(ANXA3) is a ratio of a level of RNA encoded by ANXA3 to a level of RNA encoded by ACTB in blood of the test subject, L_(CLEC4D) is a ratio of a level of RNA encoded by CLEC4D to a level of RNA encoded by ACTB in blood of the test subject, L_(IL2RB) is a ratio of a level of RNA encoded by IL2RB to a level of RNA encoded by ACTB in blood of the test subject, L_(LMNB1) is a ratio of a level of RNA encoded by LMNB1 to a level of RNA encoded by ACTB in blood of the test subject, L_(PRRG4) is a ratio of a level of RNA encoded by PRRG4 to a level of RNA encoded by ACTB in blood of the test subject, L_(TNFAIP6) is a ratio of a level of RNA encoded by TNFAIP6 to a level of RNA encoded by ACTB in blood of the test subject, and L_(VNN1) is a ratio of a level of RNA encoded by VNN1 to a level of RNA encoded by ACTB in blood of the test subject.

Further by way of example, Model #104 of Table 6 corresponds to:

P={1+ê−[4.311+(−0.659)(L _(PRRG4))]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, and L_(PRRG4) is a ratio of a level of RNA encoded by PRRG4 to a level of RNA encoded by ACTB in blood of the test subject.

TABLE 6 Logistic regression models based on blood expression levels of any possible combination of one or more of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 for determining the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer. ROC AUC values for the models are shown for the sample training set used to generate the models, as well as for an independent blind sample test set used to test the models. The models, listed in order of decreasing ROC AUC value for the training set, are based on expression levels determined via quantitative reverse transcriptase-PCR analysis using ACTB as duplex partner for normalization. The form of these models is: P = {1 + e{circumflex over ( )} − [K₀ + K₁L₁ + K₂L₂ + K₃L₃ . . . + K_(n)L_(n)]}{circumflex over ( )} − 1, where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology; K₀ is a constant; K₁ is a coefficient specific to a first gene; L₁ is a ratio of a level of RNA encoded by the first gene to a level of KNA encoded by ACTB in blood of the test subject; K₂ is a coefficient specific to a second gene; L₂ is a ratio of a level of RNA encoded by the second gene to a level of RNA encoded by ACTB in blood of the test subject; K₃ is a coefficient specific to a third gene; L₃ is a ratio of a level of RNA encoded by the third gene to a level of RNA encoded by ACTB in blood of the test subject; K_(n) is a coefficient specific to an nth gene; and L_(n) is a ratio of a level of RNA encoded by the nth gene to a level of RNA encoded by ACTB in blood of the test subject. No regression coefficients are specified for genes which are not included in the gene combination (indicated by “—”) on which a given logistic regression model is based. No. of ROC AUC Logistic genes Blind Gene-specific regression coefficient regression in Training Test Constant (K_(n)) model # model Set Set (K₀) ANXA3 CLEC4D IL2RB LMNB1 PRRG4 TNFAIP6 VNN1 1 7 0.79 0.79 0.684 −0.916 0.353 0.871 0.907 −0.968 0.154 −0.355 2 6 0.79 0.79 0.743 −0.859 0.402 0.870 0.893 −0.916 — −0.341 3 4 0.78 0.78 1.321 −0.614 0.358 0.898 — −0.749 — — 4 5 0.78 0.79 0.343 −0.907 0.322 0.829 0.737 −0.925 — — 5 5 0.78 0.78 1.814 −0.527 0.424 0.943 — −0.715 — −0.267 6 5 0.78 0.82 0.830 −0.641 — 0.883 0.935 −0.824 — −0.270 7 5 0.78 0.79 1.264 −0.658 0.318 0.898 — −0.788 0.120 — 8 5 0.78 0.82 0.359 −0.825 — 0.845 0.794 −0.927 0.189 — 9 6 0.78 0.80 0.282 −0.953 0.280 0.829 0.740 −0.965 0.123 — 10 6 0.78 0.78 1.772 −0.575 0.380 0.944 — −0.760 0.141 −0.277 11 6 0.78 0.82 0.727 −0.768 — 0.883 0.948 −0.918 0.230 −0.304 12 4 0.77 0.82 0.477 −0.716 — 0.848 0.803 −0.850 — — 13 3 0.77 0.80 1.969 — — 1.001 — −0.752 — −0.305 14 4 0.77 0.81 1.950 −0.280 — 0.966 — −0.610 — −0.189 15 4 0.77 0.78 1.915 — 0.161 1.009 — −0.840 — −0.374 16 4 0.77 0.80 1.686 — — 0.995 0.238 −0.855 — −0.363 17 5 0.77 0.79 1.748 — 0.130 1.005 0.147 −0.887 — −0.397 18 4 0.77 0.82 1.436 −0.487 — 0.925 — −0.731 0.195 — 19 4 0.77 0.80 1.934 — — 1.008 — −0.808 0.084 −0.334 20 5 0.77 0.81 1.861 −0.398 — 0.965 — −0.697 0.223 −0.218 21 5 0.77 0.79 1.907 — 0.147 1.011 — −0.852 0.029 −0.378 22 5 0.77 0.79 1.697 — — 1.001 0.207 −0.880 0.058 −0.376 23 6 0.77 0.79 1.748 — 0.121 1.006 0.142 −0.894 0.021 −0.399 24 2 0.76 0.79 1.225 — — 0.957 — −0.928 — — 25 3 0.76 0.81 1.570 −0.371 — 0.930 — −0.649 — — 26 3 0.76 0.79 1.233 — −0.006  0.957 — −0.924 — — 27 3 0.76 0.79 1.328 — — 0.960 −0.058  −0.894 — — 28 4 0.76 0.79 1.332 — 0.015 0.960 −0.072  −0.898 — — 29 3 0.76 0.79 1.249 — — 0.956 — −0.912 −0.019  — 30 4 0.76 0.79 1.244 — 0.006 0.956 — −0.914 −0.022  — 31 4 0.76 0.79 1.328 — — 0.959 −0.052  −0.890 −0.009  — 32 5 0.76 0.79 1.333 — 0.022 0.960 −0.067  −0.893 −0.016  — 33 3 0.75 0.80 0.744 −0.544 — 0.820 — — — −0.282 34 4 0.75 0.78 0.536 −0.717 0.252 0.784 — — — −0.333 35 4 0.75 0.80 0.324 −0.670 — 0.780 0.260 — — −0.313 36 5 0.75 0.78 0.241 −0.798 0.236 0.757 0.189 — — −0.353 37 5 0.75 0.75 2.890 −1.124 0.436 — 1.167 −0.723 — −0.254 38 4 0.75 0.80 0.701 −0.567 — 0.818 — — 0.033 −0.288 39 5 0.75 0.78 0.571 −0.702 0.266 0.785 — — −0.036  −0.330 40 5 0.75 0.80 0.308 −0.680 — 0.779 0.254 — 0.019 −0.316 41 6 0.75 0.78 0.271 −0.784 0.253 0.757 0.198 — −0.043  −0.349 42 6 0.75 0.76 2.851 −1.176 0.395 — 1.177 −0.767 0.134 −0.266 43 2 0.74 0.80 0.043 −0.713 — 0.751 — — — — 44 3 0.74 0.79 −0.169 −0.843 0.160 0.721 — — — — 45 3 0.74 0.80 −0.101 −0.755 — 0.738 0.076 — — — 46 4 0.74 0.79 −0.190 −0.848 0.159 0.719 0.011 — — — 47 4 0.74 0.75 2.528 −1.146 0.378 — 1.036 −0.741 — — 48 4 0.74 0.77 1.234 — −0.009  0.883 −0.489  — — −0.407 49 3 0.74 0.80 0.070 −0.701 — 0.753 — — −0.015  — 50 4 0.74 0.78 −0.082 −0.811 0.189 0.723 — — −0.068  — 51 4 0.74 0.80 −0.079 −0.742 — 0.738 0.084 — −0.021  — 52 5 0.74 0.78 −0.130 −0.824 0.187 0.719 0.028 — −0.069  — 53 5 0.74 0.76 2.481 −1.189 0.342 — 1.038 −0.778 0.110 — 54 4 0.74 0.77 1.245 — — 0.878 −0.387  — −0.120  −0.382 55 5 0.74 0.77 1.272 — 0.059 0.877 −0.424  — −0.139  −0.392 56 3 0.73 0.77 1.238 — — 0.883 −0.498  — — −0.409 57 4 0.73 0.80 3.012 −0.891 — — 1.247 −0.638 — −0.182 58 5 0.73 0.80 2.927 −1.011 — — 1.251 −0.721 0.217 −0.212 59 3 0.72 0.73 4.212 −0.733 0.451 — — −0.493 — — 60 3 0.72 0.80 2.728 −0.930 — — 1.141 −0.660 — — 61 3 0.72 0.77 0.438 — −0.175  0.826 — — — −0.505 62 4 0.72 0.73 4.547 −0.690 0.489 — — −0.466 — −0.144 63 3 0.72 0.76 0.855 — — 0.835 −0.659  — −0.188  — 64 4 0.72 0.77 0.847 — −0.031  0.836 −0.636  — −0.177  — 65 4 0.72 0.74 4.171 −0.772 0.418 — — −0.527 0.104 — 66 4 0.72 0.80 2.614 −1.040 — — 1.128 −0.735 0.188 — 67 3 0.72 0.76 0.608 — — 0.823 — — −0.217  −0.482 68 4 0.72 0.77 0.637 — −0.049  0.828 — — −0.194  −0.466 69 5 0.72 0.74 4.526 −0.731 0.455 — — −0.504 0.117 −0.154 70 2 0.71 0.76 0.786 — — 0.840 −0.871  — — — 71 3 0.71 0.78 0.770 — −0.122  0.844 −0.733  — — — 72 2 0.71 0.74 0.162 — — 0.799 — — — −0.616 73 4 0.71 0.74 2.134 −1.028 0.310 — 0.571 — — −0.286 74 5 0.71 0.74 2.164 −1.014 0.327 — 0.580 — −0.044  −0.282 75 3 0.70 0.75 1.725 −1.054 0.242 — 0.404 — — — 76 2 0.70 0.80 4.710 −0.417 — — — −0.372 — — 77 3 0.70 0.73 3.283 −0.791 0.371 — — — — −0.214 78 3 0.70 0.79 2.309 −0.868 — — 0.682 — — −0.231 79 3 0.70 0.80 4.842 −0.393 — — — −0.360 — −0.050 80 4 0.70 0.75 1.785 −1.031 0.269 — 0.421 — −0.069  — 81 3 0.70 0.80 4.558 −0.539 — — — −0.455 0.200 — 82 4 0.70 0.73 3.305 −0.783 0.378 — — — −0.020  −0.211 83 4 0.70 0.79 2.279 −0.886 — — 0.671 — 0.034 −0.237 84 4 0.70 0.81 4.759 −0.506 — — — −0.440 0.211 −0.079 85 1 0.69 0.79 3.324 −0.616 — — — — — — 86 2 0.69 0.74 2.681 −0.868 0.301 — — — — — 87 2 0.69 0.79 1.931 −0.919 — — 0.520 — — — 88 2 0.69 0.79 3.768 −0.536 — — — — — −0.126 89 2 0.69 0.79 3.214 −0.654 — — — — 0.047 — 90 3 0.69 0.73 2.748 −0.847 0.321 — — — −0.046  — 91 2 0.69 0.73 −0.674 — — 0.701 — — −0.435  — 92 3 0.69 0.76 −0.326 — −0.240  0.745 — — −0.281  — 93 3 0.69 0.79 1.931 −0.919 — — 0.520 — 0.000 — 94 3 0.69 0.80 3.648 −0.587 — — — — 0.075 −0.143 95 2 0.68 0.75 −0.764 — −0.455  0.736 — — — — 96 2 0.68 0.78 4.977 — — — — −0.524 — −0.223 97 3 0.68 0.76 4.939 — 0.113 — — −0.579 — −0.275 98 3 0.68 0.77 4.670 — — — 0.238 −0.620 — −0.289 99 4 0.68 0.76 4.716 — 0.067 — 0.185 −0.631 — −0.304 100 3 0.68 0.78 4.975 — — — — −0.531 0.012 −0.228 101 4 0.68 0.76 4.941 — 0.134 — — −0.564 −0.042  −0.268 102 4 0.68 0.77 4.655 — — — 0.255 −0.610 −0.028  −0.283 103 5 0.68 0.76 4.702 — 0.091 — 0.200 −0.615 −0.055  −0.299 104 1 0.67 0.76 4.311 — — — — −0.659 — — 105 2 0.67 0.77 4.327 — −0.010  — — −0.652 — — 106 2 0.67 0.76 4.314 — — — −0.001  −0.658 — — 107 3 0.67 0.77 4.309 — −0.014  — 0.012 −0.656 — — 108 2 0.67 0.77 4.391 — — — — −0.607 −0.062  — 109 3 0.67 0.76 4.356 — 0.035 — — −0.619 −0.079  — 110 3 0.67 0.76 4.292 — — — 0.056 −0.629 −0.074  — 111 4 0.67 0.76 4.299 — 0.024 — 0.038 −0.630 −0.082  — 112 3 0.65 0.74 3.919 — — — −0.142  — −0.152  −0.303 113 2 0.64 0.74 3.402 — −0.105  — — — — −0.397 114 2 0.64 0.75 3.927 — — — −0.277  — — −0.340 115 3 0.64 0.75 3.922 — −0.010  — −0.268  — — −0.337 116 2 0.64 0.73 3.528 — — — −0.373  — −0.206  — 117 3 0.64 0.73 3.528 — — — −0.373  — −0.206  — 118 2 0.64 0.73 3.628 — — — — — −0.189  −0.345 119 3 0.64 0.73 3.610 — 0.020 — — — −0.199  −0.352 120 4 0.64 0.73 3.951 — 0.071 — −0.188  — −0.174  −0.316 121 1 0.63 0.75 3.466 — — — −0.603  — — — 122 2 0.63 0.78 3.457 — −0.104  — −0.482  — — — 123 1 0.63 0.71 3.191 — — — — — — −0.468 124 2 0.63 0.74 2.657 — −0.133  — — — −0.269  — 125 1 0.62 0.69 2.363 — — — — — −0.357  — 126 1 0.61 0.73 2.197 — −0.338  — — — — — 127 1 0.61 0.64 −2.973 — — 0.561 — — — —

Blind sample test set: Quantitative RT-PCR analysis of gene expression in an independent blind test set of blood samples from 76 subjects having colorectal cancer and 77 subjects not having any colorectal pathology was performed as described above for the training set. The normalized RNA levels measured are shown in Table 7.

TABLE 7 Sample test set levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by ACTB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D IL2RB LMNB1 PRRG4 TNFAIP6 VNN1 CD0214pax 0 5.56 6.17 4.50 6.44 7.07 5.78 6.69 CD0242pax 0 5.87 7.32 4.54 5.43 5.19 5.87 7.38 RC2897pax 0 6.67 8.37 5.49 5.95 7.18 7.80 7.96 CD0670pax 0 7.79 5.80 3.25 6.35 7.10 8.40 7.80 CD1401pax 0 5.84 6.39 5.42 5.85 7.30 6.55 7.12 PB2924pax 0 5.56 7.17 4.12 5.97 6.51 5.90 7.12 CD0482pax 0 7.65 8.34 3.43 6.91 7.02 8.94 8.48 PB1275pax 0 5.26 6.13 5.18 5.54 7.09 5.89 8.78 CD0148pax 0 5.90 7.83 3.98 5.95 7.60 7.35 7.20 CD0122pax 0 6.55 8.40 5.02 6.38 7.07 7.96 8.83 PB2272pax 0 7.30 8.30 3.95 6.57 7.42 9.42 7.49 CD1708pax 0 6.28 9.11 4.07 5.74 6.01 7.48 7.13 CD0354pax 0 6.55 8.20 4.93 6.30 8.06 8.28 7.81 PB2634pax 0 5.76 7.74 5.28 6.80 7.20 9.18 7.39 CD0204pax 0 5.90 6.53 4.83 5.56 6.25 7.29 6.87 PB1336pax 0 7.60 9.00 6.87 6.99 7.13 8.92 9.71 RC2699pax 0 7.72 9.42 6.03 7.12 7.99 8.67 8.57 CD1278pax 0 5.95 7.57 4.20 5.72 6.31 6.83 7.36 PB2062pax 0 7.31 7.76 4.31 6.50 7.29 8.38 7.78 PB2464pax 0 5.95 8.33 4.73 5.52 5.52 6.39 8.43 CD0053pax 0 6.17 7.90 4.09 6.56 7.18 8.25 7.44 CD0192pax 0 5.49 7.60 4.19 5.66 7.38 5.48 6.03 CD0244pax 0 6.32 7.31 5.26 6.21 7.56 7.63 6.89 CD0833pax 0 5.52 8.65 4.72 5.55 6.33 6.60 5.47 CD1719pax 0 6.19 7.94 5.40 5.93 6.39 6.50 7.51 CD0036pax 0 5.20 5.95 4.60 4.95 4.51 5.99 5.82 PB2015pax 0 6.62 7.13 3.85 5.99 7.62 8.53 7.13 PB0662pax 0 6.09 7.17 5.33 6.49 7.40 7.43 6.60 PB2024pax 0 6.16 6.10 4.49 5.94 6.86 8.23 7.44 RC2565pax 0 6.63 8.81 5.94 6.33 8.38 7.11 8.75 CD1561pax 0 7.29 6.78 4.73 6.48 7.49 8.18 8.21 CD1728pax 0 7.13 6.89 4.30 6.52 7.76 7.08 8.63 CD0238pax 0 5.47 7.06 4.85 6.10 7.13 7.38 7.14 PB2342pax 0 7.65 4.19 6.21 7.29 8.02 8.00 CD0800pax 0 7.42 8.19 3.99 6.61 7.78 8.79 8.44 CD0437pax 0 4.74 5.92 5.05 4.90 5.58 6.27 6.17 RC3214pax 0 6.35 8.13 4.96 6.22 7.02 8.19 7.01 CD1487pax 0 5.24 7.83 4.51 5.99 7.26 7.36 6.48 PB1763pax 0 7.83 9.12 5.21 7.40 8.78 9.20 8.37 CD0580pax 0 5.14 5.72 3.17 4.54 4.78 6.28 5.28 CD0840pax 0 4.94 6.63 4.96 5.38 5.60 6.63 6.10 PB2757pax 0 5.32 7.54 4.98 5.51 6.48 6.77 8.12 PB2184pax 0 5.11 7.34 5.73 5.68 6.63 6.30 8.26 PB2179pax 0 5.57 6.84 4.80 5.59 5.75 5.74 6.56 PB1324pax 0 4.77 9.26 4.24 5.57 6.78 7.16 7.37 CD0237pax 0 6.46 8.06 5.42 5.89 6.89 7.51 7.26 CD1329pax 0 6.03 6.72 4.93 5.93 6.06 7.37 7.38 PB2005pax 0 7.51 7.37 4.66 6.41 7.63 9.46 8.15 PB3227pax 0 5.08 6.46 4.44 5.74 6.46 7.62 7.51 PB3163pax 0 4.51 6.23 4.17 5.32 6.10 7.12 6.54 PB3481pax 0 5.66 7.99 5.16 5.95 8.33 6.48 8.26 CD1320pax 0 4.16 5.93 4.79 4.60 5.55 5.10 6.16 RC3191pax 0 7.15 7.64 4.92 6.94 7.20 8.20 8.30 CD0583pax 0 4.29 7.00 4.44 4.16 3.96 8.82 3.97 PB3032pax 0 5.12 6.51 5.09 5.96 6.08 6.91 7.87 CD0367pax 0 5.75 6.68 4.34 5.49 6.25 7.12 7.06 PB2889pax 0 6.03 8.25 4.75 6.39 7.27 7.04 7.68 PB3524pax 0 6.66 6.73 5.40 6.83 7.72 6.07 7.38 RC2986pax 0 6.90 7.96 5.36 6.14 7.22 8.87 7.75 CD1428pax 0 6.64 9.25 3.67 5.82 7.04 7.12 6.09 RC2236pax 0 6.82 6.87 5.24 6.21 7.41 7.27 8.02 PB1918pax 0 8.72 7.41 5.20 7.28 8.29 10.44 9.02 CD0277pax 0 6.42 8.60 5.37 6.63 7.61 8.57 7.04 CD0667pax 0 5.15 6.09 5.57 5.26 6.33 6.27 6.41 CD1741pax 0 5.46 6.18 5.57 5.76 6.50 7.24 7.18 PB1973pax 0 8.07 9.15 4.68 7.12 8.89 9.13 10.01 PB1222pax 0 5.80 7.45 5.57 5.95 5.81 6.15 7.61 RC2683pax 0 8.25 9.29 5.83 6.98 8.07 9.46 9.66 PB3200pax 0 5.00 6.73 4.23 5.42 6.59 6.31 7.35 PB2130pax 0 6.31 7.61 4.91 5.50 5.79 6.48 6.81 PB3097pax 0 6.33 3.94 5.77 6.08 6.72 7.78 7.51 CD0571pax 0 5.28 6.04 3.76 5.54 6.60 6.99 5.82 CD0676pax 0 5.50 6.68 5.78 5.79 5.91 6.91 7.18 PB1514pax 0 7.57 5.96 5.35 7.38 8.09 7.63 8.37 CD0547pax 0 4.62 7.13 6.05 5.85 7.44 6.70 6.88 CD1068pax 0 5.79 6.49 4.84 6.23 7.14 8.55 6.32 CD0715pax 0 2.97 4.03 4.74 4.51 4.94 5.38 6.46 JH0130pax 1 5.32 5.90 6.01 5.47 5.77 5.93 6.90 MH0079pax 1 6.41 6.17 5.06 6.19 6.42 6.61 7.57 MH0082pax 1 7.06 4.93 5.26 6.82 6.74 8.27 7.32 AN0013pax 1 4.94 7.96 3.89 5.60 5.49 7.86 7.95 NK2005pax 1 4.20 5.83 5.59 5.08 5.65 4.02 6.98 CD1111pax 1 6.62 6.64 4.17 6.17 7.32 7.62 7.72 JH0105pax 1 5.31 7.29 4.84 5.39 5.34 7.13 8.28 MIP1007pax 1 3.42 7.30 4.89 4.27 6.00 5.13 3.62 DC0011pax 1 4.33 5.63 4.17 5.45 5.74 6.41 7.06 MH0073pax 1 4.68 6.28 5.84 4.57 5.52 6.41 5.86 DC0003pax 1 6.24 7.65 5.02 6.05 6.64 7.05 8.46 DC1002pax 1 4.62 4.35 5.41 5.26 6.40 7.24 6.90 JH0096pax 1 3.45 5.49 5.18 4.79 5.74 3.34 7.61 KW0002pax 1 4.26 6.89 4.62 4.71 4.76 5.78 6.53 JH0120pax 1 5.89 4.91 5.53 6.38 5.56 8.45 6.44 MIP1008pax 1 4.84 7.74 5.47 5.41 5.63 5.36 6.93 MIP0002pax 1 3.76 6.96 5.63 4.85 6.55 5.74 6.87 MIP1011pax 1 4.70 6.28 5.12 4.63 4.60 5.68 4.55 MH0074pax 1 5.11 5.73 5.75 5.68 6.74 7.59 6.00 DC0008pax 1 4.97 6.33 4.16 5.44 4.95 6.54 5.87 AN4014pax 1 3.93 5.76 4.25 4.58 5.76 5.20 7.74 DC0012pax 1 4.25 6.07 5.15 5.08 7.00 4.86 6.37 MIP2002pax 1 5.54 5.71 4.26 5.54 5.77 6.57 6.33 NK1005pax 1 5.76 8.79 5.22 7.02 7.38 8.60 7.55 MIP0007pax 1 2.91 3.55 6.69 3.21 4.38 3.48 4.85 JH0118pax 1 5.72 7.53 4.77 5.56 5.85 6.56 6.04 JH0089pax 1 5.11 7.30 4.99 5.68 5.58 6.54 7.38 MH0057pax 1 5.80 6.60 6.01 6.35 6.36 7.44 6.44 DC0005pax 1 5.98 7.66 4.72 6.38 6.39 7.47 7.19 MH0067pax 1 4.75 6.06 6.11 4.96 5.30 6.78 5.54 JH0085pax 1 5.19 6.48 5.92 5.99 5.76 6.65 7.12 JH0127pax 1 5.48 6.43 5.18 6.13 7.59 6.63 7.04 MIP1013pax 1 4.86 5.89 4.56 5.29 5.21 5.89 6.51 JH0126pax 1 4.21 7.08 5.35 5.68 5.40 5.50 7.07 AN4013pax 1 5.15 5.66 4.15 5.19 5.38 5.94 6.91 MH0053pax 1 7.07 8.10 4.16 6.42 5.83 8.33 7.84 JH0115pax 1 3.82 7.54 5.74 4.75 6.03 6.27 7.36 CC0004pax 1 3.83 5.81 4.59 4.67 5.46 5.50 5.84 JH0091pax 1 5.26 5.92 4.74 5.31 7.34 6.70 6.91 NK1004pax 1 5.76 7.32 6.16 5.78 6.58 7.99 7.77 NK1008pax 1 4.70 7.52 5.56 5.57 6.80 6.58 7.52 MIP2006pax 1 4.25 6.38 4.28 4.74 5.69 5.36 5.38 AN0020pax 1 4.12 6.61 5.57 4.81 4.61 4.45 6.07 JH0117pax 1 3.36 8.59 4.90 4.29 4.99 5.12 5.76 JH0100pax 1 5.54 6.69 4.86 5.66 6.57 7.23 7.26 MH0066pax 1 5.12 5.25 6.28 5.59 6.61 6.27 6.13 NK2009pax 1 5.30 5.93 4.95 5.76 5.27 7.71 5.77 NK2008pax 1 4.14 5.57 5.88 4.93 5.45 6.59 5.66 PB3067-2pax 1 5.84 8.25 4.70 6.20 6.51 7.78 6.81 NK1003pax 1 4.41 6.99 5.48 5.30 6.08 6.48 7.13 MIP1009pax 1 3.22 8.02 6.45 4.25 5.14 5.47 5.21 DC2006pax 1 6.06 5.91 4.81 5.88 6.05 7.24 7.34 JH0131pax 1 5.19 6.71 4.98 5.21 5.15 4.75 6.43 DC0015pax 1 4.95 6.98 5.01 5.46 6.53 6.02 6.17 AN0001pax 1 4.36 6.54 5.97 5.60 5.83 6.72 7.13 JH0111pax 1 5.04 6.83 4.22 5.09 6.96 7.14 5.78 MIP0005pax 1 3.74 5.56 5.98 4.46 5.80 5.74 5.33 MH0065pax 1 4.50 5.37 5.63 5.51 6.30 6.09 5.82 JH0136pax 1 3.39 4.63 6.12 4.86 5.19 7.76 4.59 CD1351pax 1 6.86 7.94 5.55 6.06 6.52 8.46 7.62 MH0075pax 1 6.05 7.17 5.57 5.77 6.75 7.32 7.27 MH0078pax 1 4.60 6.70 5.49 5.26 4.21 5.25 7.54 MH0068pax 1 7.58 5.49 4.48 6.43 7.14 8.00 6.36 MIP2003pax 1 4.24 5.60 4.30 4.93 6.05 6.85 5.97 NK2015pax 1 5.42 5.52 5.54 6.08 6.40 8.40 8.09 MH0070pax 1 5.40 7.11 4.66 5.74 6.55 7.09 7.08 JH0093pax 1 5.22 7.62 4.66 5.29 5.39 7.00 7.15 JH0135pax 1 4.40 4.64 5.52 4.62 5.38 4.31 4.62 CD1571pax 1 5.45 6.48 4.41 5.65 7.26 7.88 7.17 MH0061pax 1 4.99 5.15 5.47 5.72 6.73 7.65 7.76 NK2007pax 1 5.98 7.25 5.17 5.76 7.02 7.32 6.38 JH0132pax 1 5.29 7.18 5.29 5.76 6.96 6.66 6.83 MH0062pax 1 4.40 6.01 4.86 5.42 5.50 6.26 6.45 JH0114pax 1 4.78 6.93 7.12 5.58 7.50 5.62 5.26 CD1260pax 1 5.28 5.92 5.24 5.73 5.86 7.18 7.37 JH0022pax 1 5.00 5.94 4.73 5.49 6.17 5.66 6.80

Analysis of the test set results confirmed the surprising finding based on the training set that ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 each express RNA on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology, and that IL2RB expresses RNA on average at a significantly lower level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 8). The ranges of fold-change in the levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by ACTB in blood of the test set subjects having colorectal cancer relative to the test set subjects not having any colorectal pathology are also shown in Table 8.

TABLE 8 Sample test set ranges of fold-change in levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6, VNN1 normalized to levels of RNA encoded by ACTB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D IL2RB LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized 4.98 6.45 5.18 5.42 6.01 6.51 6.63 RNA level in subjects having colorectal cancer (ΔCt) Average normalized 6.10 7.32 4.83 6.01 6.86 7.41 7.40 RNA level in subjects not having any colorectal pathology (ΔCt) Average RNA level 2.17 1.82 0.78 1.50 1.80 1.87 1.70 fold-change p-value for average 1.7E−10 1.9E−06 1.4E−03 1.3E−07 1.6E−08 3.8E−06 4.4E−06 RNA level fold- change Maximum observed 9.13 13.66 0.20 6.98 6.26 16.78 13.78 RNA level directional fold-change

As can be seen in Table 8, a test subject having a blood level of RNA encoded by ANXA3 which is 2.2 to 9.1 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by CLEC4D which is 1.8 to 13.7 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by LMNB1 which is 1.5 to 7.0 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by PRRG4 which is 1.8 to 6.3 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by TNFAIP6 which is 1.9 to 16.8 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by VNN1 which is 1.7 to 13.8 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 8, a test subject having a blood level of RNA encoded by IL2RB which is 0.8 to 0.2 fold that of the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Furthermore, the test set results confirmed the surprising finding based on the training set that logistic regression models based on blood expression levels for any of the 127 possible combinations of one or more of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, each of which normalized against expression levels of ACTB, can be used to discriminate, with a ROC AUC of at least 0.64 (Table 6), between subjects having colorectal cancer and subjects not having any colorectal pathology. As such, the novel logistic regression models listed in Table 6 can be used to determine the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, based on blood levels of expression of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and/or VNN1.

Example 3 Measurement of Blood Levels of RNA Encoded by any Combination of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and/or VNN1 Relative to the Level of RNA Encoded by IL2RB can be Used to Determine the Probability that a Test Subject has Colorectal Cancer as Opposed to not Having any Colorectal Pathology

Materials and Methods:

Refer to “General materials and methods”, above.

Experimental Results:

Sample Training Set:

Discovery of significantly different levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, VNN1, TNFAIP6 normalized to IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology: Quantitative reverse transcriptase-PCR analysis of gene expression in a training set of blood samples from 116 subjects having colorectal cancer and 127 subjects not having any colorectal pathology, using IL2RB as duplex partner for normalization of gene expression levels was performed. The normalized RNA levels measured are shown in Table 9

TABLE 9 Sample training set levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by IL2RB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 CD0011pax 0 0.8303 1.3467 1.2008 0.8909 2.1665 2.6036 CD0012pax 0 1.2503 1.4917 0.8258 0.9309 1.9115 2.9086 CD0030pax 0 1.2878 1.2957 0.7182 1.1632 0.7535 1.7757 CD0063pax 0 2.4078 3.0807 1.6332 1.8532 3.4685 3.0157 CD0077pax 0 −0.0047 1.2417 0.7058 0.7009 0.8465 1.7436 CD0078pax 0 1.6928 2.4057 0.9432 0.9332 2.6735 1.4807 CD0085pax 0 0.4428 1.5007 0.4032 0.8232 2.4335 0.4457 CD0117pax 0 0.6028 2.2057 0.7632 2.0182 2.2585 0.6557 CD0146pax 0 0.0353 0.7117 0.6708 0.1659 1.3215 0.7236 CD0167pax 0 −1.3147 −0.1483 0.0358 0.2609 1.3315 0.0786 CD0249pax 0 −0.7797 −0.6233 −0.8142 0.0609 −0.0085 0.2486 CD0279pax 0 0.8278 1.9907 0.7632 0.7382 1.6185 1.4957 CD0286pax 0 0.0753 1.5217 0.7058 0.6659 0.7215 0.7286 CD0297pax 0 −0.1797 0.2867 0.1958 −0.3291 0.0665 0.4836 CD0323pax 0 1.7303 1.6817 0.5408 1.2359 2.2865 3.0636 CD0445pax 0 0.9878 1.2107 0.6682 0.6932 1.8085 1.6907 CD0463pax 0 −0.3647 1.2267 0.3058 0.5559 1.2365 1.0136 CD0491pax 0 −0.3972 0.3507 0.4482 0.7032 1.1785 0.2907 CD0496pax 0 0.8753 2.4167 0.6958 1.4509 1.0515 0.6436 CD0501pax 0 0.8753 1.7517 0.9558 0.9109 2.7615 1.0986 CD0504pax 0 −0.4947 0.2367 0.2358 1.0209 0.3715 0.7936 CD0573pax 0 1.9978 1.3107 0.9582 0.9982 2.4435 1.9357 CD0578pax 0 1.6103 1.7317 0.6408 0.6259 1.6865 1.7136 CD0639pax 0 0.1028 0.6657 0.6232 −0.2618 0.9985 1.5857 CD0645pax 0 −0.8347 −0.1883 −0.4342 −0.4441 0.4965 0.0986 CD0679pax 0 0.4703 1.7767 0.6658 0.5659 1.9465 2.2636 CD0685pax 0 0.8753 2.3317 0.8008 1.3759 2.1915 1.4836 CD0716pax 0 1.9978 2.4057 0.9182 0.4432 1.5835 2.0457 CD0749pax 0 0.3303 1.3717 0.4058 0.5509 2.0465 1.0336 CD0760pax 0 −2.5747 −1.3583 −1.9442 −1.1491 −1.2335 −0.8714 CD0811pax 0 2.2353 2.8417 1.1858 1.3609 1.3865 1.3286 CD0846pax 0 −0.6522 0.3407 −0.6418 −0.3468 −0.6315 1.5657 CD0848pax 0 0.7278 1.2057 0.9832 1.0232 1.5785 1.8307 CD0924pax 0 0.1428 0.5357 −0.0768 −0.4418 0.2935 −0.0793 CD1066pax 0 0.1753 0.6667 0.2658 0.2059 1.9715 0.5786 CD1073pax 0 0.1053 −0.0633 −0.0092 −0.1341 0.8015 1.0886 CD1075pax 0 −0.3322 0.4757 −0.0118 1.1582 1.2385 0.1957 CD1089pax 0 −1.1072 0.1657 −0.7818 −0.5318 0.1935 −0.1193 CD1116pax 0 −0.2072 −0.0543 −0.2818 0.2982 1.4885 0.4107 CD1120pax 0 −0.8872 0.0357 −0.5868 0.2032 1.1885 −0.2443 CD1198pax 0 0.5253 0.5317 0.7908 0.7509 0.7915 0.9786 PB1179pax 0 1.0003 1.0617 0.8808 0.9909 2.4315 1.2286 PB1277pax 0 0.8803 1.4817 0.4258 0.9859 1.5765 0.8286 PB1301pax 0 −1.7247 −0.9183 −0.9092 −0.5091 −0.6985 −1.2864 PB1315pax 0 −1.5572 0.2257 −0.6218 −0.3118 −0.2015 0.9007 PB1345pax 0 0.1953 0.6617 0.7508 1.0459 0.3615 2.0236 PB1518pax 0 1.2653 1.6967 0.2058 0.8359 1.3565 1.3036 PB1520pax 0 1.0953 2.0267 0.9708 0.0109 1.6565 2.2236 PB1574pax 0 1.0753 1.5467 0.8008 0.6109 1.0465 1.1836 PB1783pax 0 1.5978 1.7007 1.1982 1.2632 2.1135 1.5907 PB1799pax 0 0.6978 1.0157 0.5282 1.0632 2.0785 0.5957 PB1811pax 0 0.8628 1.4057 0.8232 1.2632 1.3685 0.9507 PB1830pax 0 0.1428 0.6807 0.2532 0.1182 0.8985 2.3407 PB1833pax 0 0.2028 1.1407 0.4782 0.5532 0.9385 1.5457 PB1843pax 0 0.5553 0.4717 0.0708 0.5909 −0.5285 1.1486 PB1851pax 0 0.4428 0.1007 0.2632 0.3232 2.7035 1.6007 PB1919pax 0 1.4703 2.1067 0.8108 1.7959 2.1365 2.5086 PB1922pax 0 0.3103 1.1867 0.4258 1.3759 2.1215 0.9986 PB1924pax 0 0.2428 0.5357 0.1632 0.3632 1.1535 1.2357 PB1937pax 0 1.3128 2.1057 1.0982 2.9132 2.4835 2.2007 PB1964pax 0 0.4828 2.6207 0.7382 1.5332 2.4035 2.7507 PB2027pax 0 −0.1422 0.3857 0.1582 0.3182 1.1835 1.5807 PB2029pax 0 0.1953 0.5917 0.0708 −0.0391 1.8615 0.7336 PB2073pax 0 0.4478 0.9057 0.4382 1.6632 1.5085 0.9257 PB2086pax 0 0.1153 0.1817 0.3108 0.8409 6.3215 0.5386 PB2099pax 0 −0.4622 −0.5993 −0.1568 0.0732 −0.1265 0.1057 PB2100pax 0 1.1628 1.1057 0.6532 1.5482 2.1385 1.1507 PB2132pax 0 0.5503 1.1517 0.3558 0.6109 2.1315 1.4536 PB2168pax 0 1.3278 1.5357 0.8482 1.1682 2.3435 1.3307 PB2192pax 0 0.3153 0.8967 0.3308 −0.0291 1.2515 1.9286 PB2196pax 0 0.8328 1.6107 0.7932 1.4432 2.0535 1.2107 PB2200pax 0 1.1028 1.4807 0.3732 0.4432 0.9635 0.5757 PB2213pax 0 2.1753 2.2717 1.1658 0.9009 3.1465 1.9736 PB2224pax 0 −0.2772 0.6207 0.0482 0.3582 2.1235 1.2607 PB2228pax 0 1.7703 2.1017 1.3658 1.6859 3.6965 2.7186 PB2229pax 0 −0.2047 −0.3183 −0.0542 −0.9241 0.5615 −0.1764 PB2277pax 0 1.3578 0.8507 0.6332 0.3582 1.0785 1.7457 PB2297pax 0 0.4178 1.1507 0.1282 0.0332 0.9235 −0.3343 PB2312pax 0 1.3628 2.0057 1.4132 0.9632 2.0885 2.0357 PB2398pax 0 −0.5822 0.1007 −0.2868 −0.7518 −0.1865 1.3307 PB2409pax 0 0.1153 0.6817 0.3008 0.3359 1.0115 1.5036 PB2414pax 0 2.7128 2.3707 1.2132 2.1832 3.6985 1.9707 PB2467pax 0 0.7478 1.1457 0.5482 0.6382 2.2385 1.3607 PB2473pax 0 0.3828 0.8857 0.4432 1.0932 0.9185 1.8407 PB2512pax 0 0.7003 1.7267 0.8458 0.4709 1.8115 2.0136 PB2568pax 0 −0.4772 0.0157 −0.3718 0.4132 1.2435 1.0857 PB2571pax 0 0.3003 1.0017 0.5558 0.2609 1.8915 1.9336 PB2603pax 0 1.0128 1.4757 1.1082 1.1632 2.3335 0.7457 PB2624pax 0 0.4403 0.5167 0.7208 1.3259 1.3865 1.2286 PB2824pax 0 0.5178 0.9907 0.4582 1.0132 1.8135 1.3207 PB2880pax 0 1.0403 1.0617 0.6208 −0.2491 1.8615 1.5586 PB3088pax 0 1.6503 1.7517 1.3208 1.1359 3.4165 2.3786 RC0882pax 0 0.2728 1.4507 0.6582 0.7682 2.0985 1.8007 RC0888pax 0 −0.7872 −0.3193 −0.2118 0.2932 0.7835 0.2957 RC0968pax 0 −0.8522 −0.6493 0.0182 1.4382 0.7835 2.1457 RC2114pax 0 −0.4722 0.7557 0.0282 0.4132 0.1335 1.9357 RC2238pax 0 0.9528 1.8557 0.5982 1.5182 2.4435 2.8857 RC2681pax 0 0.3278 1.1957 0.4582 0.5532 0.7435 0.9507 RC2703pax 0 1.6403 1.8317 0.7658 1.1959 1.1615 1.1436 RC2749pax 0 0.3978 1.1407 0.3632 0.4682 1.6635 1.5157 RC2750pax 0 −1.7872 −1.2393 −1.0418 −0.3118 −0.1115 −0.6943 RC2756pax 0 1.3803 0.9167 0.5508 1.0009 1.6415 1.9636 RC2771pax 0 −0.9547 0.3567 −0.6792 −0.3341 1.1965 1.4536 RC2790pax 0 0.8953 0.9817 0.4808 0.7259 1.0815 1.3536 RC2792pax 0 1.2903 0.8667 0.8058 1.4559 1.9415 1.5836 RC2808pax 0 0.7953 1.9117 0.7558 1.0009 1.1715 1.4036 RC2822pax 0 0.7728 1.2607 0.3282 0.5932 2.5785 0.5807 RC2834pax 0 −0.6247 0.2917 −0.5742 0.9309 2.0765 0.9236 RC2871pax 0 0.9028 1.4107 1.1032 1.5332 2.6485 2.6307 RC2879pax 0 −0.2047 0.3867 −0.0342 0.8509 0.6315 0.5086 RC2892pax 0 −0.0022 0.5557 −0.0968 0.7032 2.0385 1.1857 RC2895pax 0 1.7178 1.9857 1.2632 1.3682 1.4435 2.0557 RC2921pax 0 1.3153 1.2967 1.0058 1.3709 2.0315 2.0886 RC2958pax 0 1.0553 1.1017 0.4958 0.1409 0.4965 1.4836 RC3022pax 0 0.3028 0.3007 0.3582 1.0432 1.7635 0.4707 RC3112pax 0 1.2553 1.4667 0.5908 0.5759 2.5515 1.3286 RC3146pax 0 −0.1572 −0.2793 −0.4918 0.1432 1.0235 0.8307 RC3184pax 0 2.1353 2.5967 1.0758 1.3559 2.2865 2.2336 RC3232pax 0 −0.3747 0.5667 −0.5942 0.5309 −0.4385 2.3786 RC3324pax 0 0.2128 0.8557 0.0082 0.3282 1.3985 −0.0693 RC3327pax 0 0.2003 −0.1333 −0.0292 −0.2491 1.2315 1.8086 RC3355pax 0 0.0328 0.5657 −0.2668 −0.0418 1.2935 0.4857 RC3380pax 0 −0.4372 0.4907 −0.3518 −0.0318 0.5235 0.0757 RC3413pax 0 0.6028 1.1907 0.4532 0.0182 0.8435 2.3907 RC3421pax 0 −0.0047 0.2917 −0.0142 0.1409 −0.0735 −0.0964 RC3468pax 0 −0.1022 −0.0143 −0.0618 −0.3368 1.1485 0.2907 RC3498pax 0 0.0353 −0.2633 −0.1892 0.2909 1.2415 0.2486 CC0003pax 1 −1.4122 −0.3593 −0.9318 −0.6468 0.8435 −0.8893 CD0157pax 1 1.5153 1.5517 1.1308 1.3209 3.0715 2.8186 CD0164pax 1 −0.0247 0.4667 0.6758 1.0059 2.5315 1.2886 CD0256pax 1 −0.6322 0.0807 0.0032 0.0382 0.8935 1.1557 CD0322pax 1 −1.1572 −0.4693 −0.8368 −0.2818 0.5435 1.0507 CD0356pax 1 −0.6772 −1.1393 −0.7718 −0.8668 −0.2215 −1.1643 CD0371pax 1 0.1028 0.9607 −0.1918 −0.3018 0.8385 −0.2843 CD0629pax 1 −0.0772 0.5407 0.5382 1.3882 0.2885 1.2507 CD1050pax 1 0.8153 0.1417 0.2208 0.7559 1.3815 1.0836 DC0001pax 1 0.1353 −0.4183 0.1208 −0.0941 0.3065 0.0936 DC0002pax 1 0.9878 0.2857 0.3632 −0.1718 1.7035 0.9057 DS0003pax 1 −1.8347 −0.7183 −1.5192 −1.5591 −0.3485 0.6886 FC0005pax 1 0.0928 0.1507 0.2682 0.1732 0.4235 1.8157 FC0011pax 1 −0.4572 −0.0793 −0.1118 −0.2318 0.8635 0.2707 FC0012pax 1 −2.5847 −0.4033 −1.3792 −1.2541 −0.2885 −0.3614 JGA0001pax 1 −2.3247 −1.6483 −1.5592 −0.7241 −1.2535 −1.1814 JGA0008pax 1 −0.6772 1.0357 0.5732 0.0932 0.8485 0.7057 JH0002pax 1 0.5453 0.9667 0.5608 0.4459 1.4065 0.7586 JH0003pax 1 0.2853 0.1667 −0.2292 −0.3941 −0.1385 1.0886 JH0004pax 1 −0.1747 −0.1733 −0.3592 −0.5591 1.1515 0.6686 JH0005pax 1 0.0928 1.2207 0.0682 0.1482 1.5735 1.1757 JH0006pax 1 −0.6397 0.0667 −0.2692 −0.2741 0.8715 −0.3114 JH0007pax 1 −2.6372 −2.2043 −1.6168 −0.5018 −0.0865 −1.2993 JH0008pax 1 0.5453 2.4167 0.2208 0.8859 2.1315 0.6336 JH0009pax 1 −0.8522 −0.7793 −0.0968 −0.6668 −0.1815 0.4507 JH0010pax 1 −0.3847 0.6517 0.2208 0.3059 0.6365 −0.2664 JH0012pax 1 −0.1072 0.3857 0.2882 0.0432 0.6685 0.9807 JH0013pax 1 −0.3022 0.2007 −0.3118 −0.0568 2.0485 0.8357 JH0014pax 1 1.1828 1.2107 0.3182 −0.0418 2.0485 2.5207 JH0016pax 1 0.5053 0.9167 0.6658 0.2659 0.4715 0.8636 JH0018pax 1 −1.1972 −0.1493 −0.4268 −0.4318 −0.1465 0.3207 JH0019pax 1 0.1153 0.6267 0.0558 −0.2091 0.1565 0.1936 JH0020pax 1 0.2728 2.0207 0.7332 −0.1518 0.7585 1.3107 JH0021pax 1 −0.8297 0.7867 −0.3992 −0.8541 0.2615 0.0586 JH0023pax 1 −0.2272 1.3307 0.5182 1.6882 1.2985 1.9507 JH0024pax 1 1.0653 2.5467 1.2508 1.4159 3.3465 2.9786 JH0025pax 1 −0.7847 −0.3833 −0.4292 −0.8891 −0.2435 0.5136 JH0026pax 1 −1.1522 0.5857 −0.0418 −0.3468 1.1035 1.1507 JH0027pax 1 −3.3947 −2.5983 −2.3842 −2.0791 −2.3435 −1.8814 JH0028pax 1 0.3253 1.0967 0.9908 0.7459 2.5415 1.4586 JH0029pax 1 −1.3522 −0.6093 −0.5918 −0.7818 −0.5615 0.5557 JH0031pax 1 −0.7297 0.2817 −0.2092 −0.2791 0.5615 0.5136 JH0032pax 1 1.5478 1.7557 0.4532 0.3732 1.7785 1.8307 JH0033pax 1 −0.8797 1.0817 −0.4242 −0.6141 1.3865 −0.1914 JH0034pax 1 −0.5397 1.0667 0.4908 0.3909 1.5465 1.5186 JH0035pax 1 −0.3222 1.3857 0.2782 −0.3268 1.9385 0.8207 JH0036pax 1 0.8128 1.0107 0.4032 0.2182 1.9235 1.1757 JH0038pax 1 0.3103 1.5367 0.2258 0.4109 2.1215 0.8386 JH0039pax 1 0.5278 0.6207 0.5032 1.1232 3.1135 0.0857 JH0040pax 1 0.4353 0.8117 0.5508 0.3259 1.2465 0.8636 JH0041pax 1 0.7303 1.7117 0.4508 0.2759 1.9565 1.0436 JH0042pax 1 −2.2922 −0.6293 −1.2268 −0.7568 −1.0515 −1.7443 JH0043pax 1 −0.8022 −0.1993 −0.2918 −0.9318 −0.3015 −0.2393 JH0046pax 1 −0.0447 0.0567 0.6408 −0.2541 0.8965 0.0336 JH0047pax 1 0.1728 1.9907 0.6082 1.2782 1.6085 2.0757 JH0051pax 1 −0.9647 −0.1533 −0.3892 −1.0491 −0.2135 −0.4064 JH0052pax 1 −0.6597 0.3067 −0.4442 −0.9141 −0.4585 −0.7914 JH0053pax 1 −0.9522 −0.1693 −0.5918 −0.0318 −0.2515 0.1107 JH0057pax 1 −0.1872 1.9757 0.1432 0.6682 1.4335 1.2057 JH0059pax 1 −0.7897 0.0717 −0.3442 −0.3241 0.3215 0.1136 JH0060pax 1 −1.0122 0.1207 −0.2818 0.0482 0.3385 0.3557 JH0061pax 1 0.7803 2.5567 0.5558 1.0309 3.2565 0.3136 JH0063pax 1 −0.2197 1.0467 0.2458 −0.4141 0.8115 2.0486 JH0065pax 1 −2.7497 −1.4333 −2.0542 −2.8691 −1.5035 −0.4814 JH0066pax 1 −1.1972 −0.0343 −0.8418 −1.6318 −1.0715 −0.4643 JH0068pax 1 0.3653 0.8867 0.7108 0.4809 1.7165 2.1986 JH0069pax 1 −0.6447 0.3967 −0.0892 −0.1791 −0.0735 −0.4014 JH0071pax 1 −2.3272 −2.1943 −1.6968 −1.0318 −1.2715 −0.3743 JH0072pax 1 −0.1197 −0.7533 −0.0892 −0.6741 1.1515 0.0586 JH0077pax 1 −0.3022 0.2957 0.0882 −0.0368 0.4435 1.6307 JH0078pax 1 1.2953 1.2767 1.2058 0.2609 1.2165 1.2786 JH0080pax 1 −2.1122 −1.1393 −1.0418 −0.7568 −1.5315 0.3507 JH0082pax 1 −0.6722 −0.5393 −0.0518 −0.2368 −0.3065 1.0857 JH0083pax 1 −1.3997 −0.0133 −0.3542 −1.2991 0.3115 0.7236 JH0086pax 1 0.2553 0.1667 0.0158 −0.7941 0.4015 1.1086 JH0092pax 1 −0.2647 1.6167 0.2158 0.2559 0.1565 1.3386 MH0001pax 1 1.1653 1.7717 1.0908 1.1159 2.8015 1.9086 MH0009pax 1 −0.4972 −0.0193 −0.7268 −0.5768 −0.3015 −0.3493 MH0012pax 1 −0.1347 1.0017 0.3658 0.8559 0.9765 0.9186 MH0014pax 1 0.8278 1.4457 0.8482 0.5432 3.0535 1.8007 MH0016pax 1 −1.1672 −0.8793 −0.9168 −1.2168 −0.4165 −0.7243 MH0017pax 1 0.3403 1.4267 0.5658 −0.0241 1.7565 2.0536 MH0018pax 1 1.2128 0.7657 0.3232 0.3682 2.1235 0.7057 MH0021pax 1 0.8103 0.2517 −0.3192 0.0709 1.6865 1.7086 MH0022pax 1 0.6903 1.3667 0.6308 0.5459 1.2515 1.4236 MH0024pax 1 0.2228 0.4757 −0.0568 −0.1768 0.0635 0.9057 MH0026pax 1 −1.2897 0.0417 −0.4392 0.1059 −0.3935 −0.1914 MH0028pax 1 −0.0272 0.3557 −0.1068 −0.8368 −0.0765 −0.0493 MH0029pax 1 −0.0697 0.0167 0.0658 −0.6641 1.0215 0.3536 MH0035pax 1 0.6603 2.0217 0.9458 0.7759 1.0965 1.4036 MH0037pax 1 −0.1697 1.0717 −0.0342 0.1309 1.1665 1.6186 MH0038pax 1 1.7453 1.5967 1.3108 1.4609 2.2365 2.3736 MH0039pax 1 −1.1922 −0.3093 −0.1218 −0.5718 −0.0965 0.5557 MH0042pax 1 −0.1522 0.0657 0.2332 −0.1318 −0.0815 0.9357 MH0050pax 1 −1.4222 0.5507 −0.6818 −0.3468 0.8885 1.6307 MH0051pax 1 −1.2197 −1.0683 −0.7092 −1.6041 −2.1735 −0.1814 MIP0004pax 1 −2.1722 −2.1793 −1.4118 −1.1218 −0.9865 −2.2593 MP0013Apax 1 0.4028 1.2307 0.0782 0.2282 1.4535 0.1557 MP0014Bpax 1 −0.4347 0.6117 −0.5542 −0.0441 1.2765 −0.1964 MP0018Apax 1 −1.0022 −0.4193 −0.9668 −1.5668 −0.3165 −1.4293 MP0019Bpax 1 −0.6222 −0.2993 −0.3768 −0.6268 −0.3465 0.8757 MP0024pax 1 −1.2597 −0.2333 −0.4542 0.1409 1.3465 0.7386 NK2001pax 1 −0.8347 −0.1233 −0.6992 −1.5741 −0.0785 1.1036 NK2002pax 1 0.0203 −0.0183 0.1908 −0.4741 0.8115 0.9786 NK2003pax 1 −0.7372 0.0407 −0.3218 −0.2868 1.2085 −0.1993 NK2004pax 1 −0.9022 0.3107 −0.5118 −0.9568 0.5285 −0.3843 PB1829pax 1 0.3378 1.5057 0.0682 0.0782 1.5485 1.7407 PB1842pax 1 1.0953 1.3467 0.8708 0.2009 2.3265 0.9536 PB1872pax 1 0.3928 0.6507 0.5682 −0.5068 1.2035 0.1807 PB2857pax 1 −0.9422 0.5057 −0.3968 0.2982 −0.2165 0.8657 RC2919pax 1 2.0678 2.0357 1.6382 3.0282 2.8985 3.9757 RC3062pax 1 0.1453 0.5917 0.1408 0.3759 0.1365 0.3386 RC3277pax 1 −0.1122 0.1707 −0.0568 −0.0168 0.7285 0.2457 RC3297pax 1 0.2078 0.9457 0.4032 0.5332 2.7135 0.9807 RC3445pax 1 −0.8497 −0.1233 −0.3442 −0.7391 0.6765 0.3086 RC3467pax 1 2.0928 2.9557 1.5782 1.4332 2.8485 2.8457

Surprisingly, analysis of the data showed that RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 is present on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 10). The ranges of fold-change in the levels of RNA encoded by these genes normalized to levels of RNA encoded by IL2RB in blood of the training set subjects having colorectal cancer relative to the training set subjects not having any colorectal pathology are shown in Table 10.

TABLE 10 Sample training set ranges of fold-change in levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized RNA level in −0.30 0.42 −0.05 −0.12 0.79 0.66 subjects having colorectal cancer (ΔCt) Average normalized RNA level in 0.46 0.99 0.39 0.65 1.42 1.25 subjects not having any colorectal pathology (ΔCt) Average RNA level fold-change 1.69 1.48 1.55 1.35 1.55 1.35 p-value for average RNA level fold- 5.5E−09 5.5E−06 6.4E−07 2.5E−13 6.0E−06 2.7E−06 change Maximum observed RNA level 14.43 12.01 6.83 11.46 13.58 11.36 directional fold-change

As can be seen in Table 10, a test subject having a blood level of RNA encoded by ANXA3, normalized to a level of RNA encoded by IL2RB, which is 1.7 to 14.4 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 10, a test subject having a blood level of RNA encoded by CLEC4D, normalized to a level of RNA encoded by IL2RB, which is 1.5 to 12.0 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 10, a test subject having a blood level of RNA encoded by LMNB1, normalized to a level of RNA encoded by IL2RB, which is 1.5 to 6.8 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 10, a test subject having a blood level of RNA encoded by PRRG4, normalized to a level of RNA encoded by IL2RB, which is 1.3 to 11.5 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 10, a test subject having a blood level of RNA encoded by TNFAIP6, normalized to a level of RNA encoded by IL2RB, which is 1.5 to 13.6 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 10, a test subject having a blood level of RNA encoded by VNN1, normalized to a level of RNA encoded by IL2RB, which is 1.3 to 11.4 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Generation of logistic regression models for determining the probability that a test subject has colorectal cancer versus not having any colorectal pathology via measurement of levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB: Linear regression analysis of levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to IL2RB surprisingly showed that logistic regression models could be generated, based on blood expression levels normalized to IL2RB for all 63 possible combinations of one or more of these genes, for discriminating, with a ROC AUC of at least 0.67, between subjects having colorectal cancer and subjects not having any colorectal pathology. Examples of these logistic regression models are shown in Table 11. A logistic regression model based on ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 (Table 11, Model #128) was surprisingly found to enable discrimination between subjects having colorectal cancer and subjects not having any colorectal pathology with a ROC AUC of 0.80.

By way of example, Model #128 of Table 11 corresponds to:

P={1+ê−[(−0.196)+(−1.042)(L _(ANXA3))+(0.393)(L _(CLEC4D))+(1.272)(L _(LMNB1))+(−1.837)(L _(PRRG4))+(0.289)(L _(TNFAIP6))+(−0.153)(L _(VNN1))]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, where L_(ANXA3) is a ratio of a level of RNA encoded by ANXA3 to a level of RNA encoded by IL2RB in blood of the test subject, L_(CLEC4D) is a ratio of a level of RNA encoded by CLEC4D to a level of RNA encoded by IL2RB in blood of the test subject, L_(LMNB1) is a ratio of a level of RNA encoded by LMNB1 to a level of RNA encoded by IL2RB in blood of the test subject, L_(PRRG4) is a ratio of a level of RNA encoded by PRRG4 to a level of RNA encoded by IL2RB in blood of the test subject, L_(TNFAIP6) is a ratio of a level of RNA encoded by TNFAIP6 to a level of RNA encoded by IL2RB in blood of the test subject, and L_(VNN1) is a ratio of a level of RNA encoded by VNN1 to a level of RNA encoded by IL2RB in blood of the test subject.

Further by way of example, Model #157 of Table 11 corresponds to:

P={1+ê−[0.288+(−1.392)(L _(PRRG4))]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, and L_(PRRG4) is a ratio of a level of RNA encoded by PRRG4 to a level of RNA encoded by IL2RB in blood of the test subject.

TABLE 11 Logistic regression models based on blood expression levels for any possible combination of one or more of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, normalized to IL2RB expression levels for determining the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer. ROC AUC values for the models are shown for the sample training set used to generate the models, as well as for an independent blind sample test set used to test the models. The models, listed in order of decreasing ROC AUC value for the training set, are based on expression levels determined via quantitative reverse transcriptase-PCR analysis using IL2RB as duplex partner for normalization. The form of these models is: P = {1 + e{circumflex over ( )} − [K₀ + K₁L₁ + K₂L₂ + K₃L₃ . . . + K_(n)L_(n)]}{circumflex over ( )} − 1, where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology; K₀ is a constant; K₁ is a coefficient specific to a first gene; L₁ is a ratio of a level of RNA encoded by the first gene in blood to a level of RNA encoded by IL2RB in blood; K₂ is a coefficient specific to a second gene; L₂ is a ratio of a level of RNA encoded by the second gene in blood to a level of RNA encoded by IL2RB in blood; K₃ is a coefficient specific to a third gene; L₃ is a ratio of a level of RNA encoded by the third gene in blood to a level of RNA encoded by IL2RB in blood; K_(n) is a coefficient specific to an nth gene; and L_(n) is a ratio of a level of RNA encoded by the nth gene in blood to a level of RNA encoded by IL2RB in blood. No regression coefficients are specified for genes which are not included in the gene combination (indicated by “—”) on which a given logistic regression model is based. No. of Logistic genes ROC AUC Gene-specific regression coefficient Regression in Training Constant (K_(n)) Model # Model Set Test Set (K₀) ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 128 6 0.80 0.78 −0.196 −1.042 0.393 1.272 −1.837 0.289 −0.153 129 5 0.80 0.79 −0.298 −1.058 0.366 1.187 −1.854 0.285 — 130 5 0.80 0.79 0.034 −0.945 0.456 1.300 −1.715 — −0.146 131 5 0.79 0.78 −0.070 −0.937 — 1.469 −1.774 0.336 −0.115 132 4 0.79 0.79 −0.065 −0.961 0.428 1.221 −1.733 — — 133 4 0.79 0.78 −0.154 −0.955 — 1.394 −1.790 0.330 — 134 5 0.79 0.78 −0.305 −0.630 0.575 — −1.632 0.311 −0.049 135 4 0.79 0.78 0.229 −0.799 — 1.537 −1.620 — −0.097 136 4 0.79 0.79 −0.337 −0.645 0.562 — −1.642 0.309 — 137 4 0.79 0.78 −0.058 −0.516 0.645 — −1.493 — −0.041 138 5 0.79 0.76 0.239 — 0.173 0.355 −1.782 0.144 −0.210 139 3 0.79 0.78 0.153 −0.817 — 1.474 −1.637 — — 140 3 0.79 0.79 −0.085 −0.528 0.634 — −1.503 — — 141 4 0.79 0.76 0.128 — 0.280 — −1.707 0.174 −0.162 142 4 0.79 0.76 0.337 — 0.216 0.413 −1.721 — −0.203 143 3 0.79 0.77 0.229 — 0.355 — −1.615 — −0.144 144 4 0.79 0.76 0.279 — — 0.492 −1.757 0.172 −0.189 145 4 0.78 0.76 0.109 — 0.128 0.225 −1.802 0.134 — 146 3 0.78 0.76 0.053 — 0.209 — −1.747 0.157 — 147 3 0.78 0.76 0.416 — — 0.607 −1.673 — −0.173 148 3 0.78 0.76 0.206 — 0.169 0.285 −1.745 — — 149 3 0.78 0.76 0.150 — — 0.339 −1.781 0.156 — 150 2 0.78 0.77 0.153 — 0.285 — −1.659 — — 151 2 0.78 0.76 0.284 — — 0.457 −1.703 — — 152 3 0.78 0.76 0.123 — — — −1.591 0.257 −0.078 153 3 0.78 0.77 −0.102 −0.352 — — −1.463 0.390 — 154 4 0.78 0.77 −0.130 −0.368 — — −1.474 0.388 0.037 155 2 0.78 0.76 0.082 — — — −1.630 0.237 — 156 3 0.77 0.77 0.216 −0.179 — — −1.276 — 0.061 157 1 0.77 0.76 0.288 — — — −1.392 — — 158 2 0.77 0.77 0.267 −0.150 — — −1.256 — — 159 2 0.77 0.76 0.296 — — — −1.384 — −0.011 160 5 0.73 0.75 0.162 −0.907 0.153 0.321 — −0.073  −0.270 161 4 0.73 0.75 0.108 −0.930 0.130 0.296 — — −0.273 162 3 0.73 0.76 0.086 −0.818 0.185 — — — −0.243 163 4 0.73 0.76 0.125 −0.793 0.206 — — −0.055  −0.238 164 4 0.72 0.75 0.208 −0.868 — 0.406 — −0.046  −0.254 165 3 0.72 0.75 0.167 −0.888 — 0.380 — — −0.258 166 2 0.72 0.75 0.171 −0.698 — — — — −0.204 167 3 0.72 0.75 0.179 −0.691 — — — −0.009  −0.203 168 3 0.72 0.76 −0.021 −0.870 0.134 — — −0.077  — 169 4 0.72 0.76 −0.012 −0.929 0.103 0.155 — −0.087  — 170 2 0.72 0.77 −0.080 −0.907 0.102 — — — — 171 1 0.72 0.76 −0.014 −0.827 — — — — — 172 2 0.72 0.76 0.031 −0.793 — — — −0.043  — 173 3 0.72 0.76 −0.079 −0.957 0.074 0.122 — — — 174 2 0.72 0.76 −0.039 −0.932 — 0.178 — — — 175 3 0.72 0.76 0.026 −0.902 — 0.221 — −0.068  — 176 3 0.71 0.72 0.514 — — −0.502  — −0.191  −0.309 177 4 0.71 0.72 0.519 — −0.024  −0.482  — −0.186  −0.306 178 3 0.70 0.72 0.398 — −0.097  −0.604  — — −0.319 179 2 0.70 0.73 0.361 — — −0.706  — — −0.333 180 2 0.70 0.70 0.727 — — — — −0.345  −0.451 181 3 0.70 0.71 0.701 — −0.192  — — −0.256  −0.383 182 2 0.70 0.73 0.306 — — −0.769  — −0.227  — 183 3 0.69 0.73 0.331 — −0.085  −0.690  — −0.208  — 184 1 0.69 0.73 0.102 — — −1.041  — — — 185 2 0.69 0.70 0.589 — −0.367  — — — −0.433 186 2 0.69 0.73 0.186 — −0.170  −0.838  — — — 187 1 0.68 0.69 0.552 — — — — — −0.671 188 2 0.68 0.72 0.548 — −0.379  — — −0.331  — 189 1 0.67 0.70 0.549 — — — — −0.576  — 190 1 0.67 0.71 0.371 — −0.649  — — — —

Blind sample test set: Quantitative reverse transcriptase-PCR analysis of expression of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 in an independent test set of blood samples from 165 subjects having colorectal cancer and 171 subjects not having any colorectal pathology was performed as described above for the training set. The normalized RNA levels measured are shown in Table 12.

TABLE 12 Sample test set levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by IL2RB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 CD0036pax 0 −0.0922 −0.0443 −0.1868 −1.0168 0.5035 −0.0543 CD0053pax 0 1.1828 2.1407 1.5032 1.3032 2.9135 1.5907 CD0092pax 0 1.2028 0.9057 0.8232 0.6032 1.6285 0.2907 CD0108pax 0 −0.0522 −0.1893 0.2582 −0.1318 0.3385 0.2757 CD0122pax 0 0.5628 1.2857 0.5582 0.6382 2.0485 1.9357 CD0148pax 0 0.6778 2.0057 0.6732 1.4432 2.0335 1.5607 CD0192pax 0 0.6878 0.8157 0.7682 1.5882 0.7085 0.8907 CD0204pax 0 0.1978 0.6907 0.0782 −0.1418 1.0185 0.9557 CD0214pax 0 0.4478 0.1557 1.1682 1.1932 0.6235 0.6157 CD0237pax 0 0.3828 0.8707 −0.0168 0.0582 1.1685 0.8007 CD0238pax 0 0.2428 0.8957 0.3982 1.0232 1.5385 0.9657 CD0242pax 0 0.9528 1.3957 0.5082 −0.3818 0.9685 1.0307 CD0244pax 0 0.4928 0.3507 0.4182 0.8982 1.4535 −0.0493 CD0277pax 0 0.1453 1.7617 0.2358 0.4909 1.8265 0.1486 CD0282pax 0 −0.1572 0.2207 −0.2118 0.0632 0.7585 −1.2243 CD0295pax 0 0.1578 0.7957 0.5482 0.5332 1.1735 0.1907 CD0354pax 0 0.5178 0.9557 0.2432 1.0732 1.6235 1.0307 CD0367pax 0 0.7778 0.6857 0.5232 0.3432 1.8935 0.8457 CD0369pax 0 1.0328 2.1057 0.9982 1.9532 2.1885 1.7607 CD0398pax 0 2.1128 2.2157 1.6682 2.0432 3.7635 3.1407 CD0409pax 0 −0.2272 0.7757 0.0282 0.7082 0.5735 1.2357 CD0419pax 0 0.2503 0.9617 0.5758 0.3759 2.1815 −0.3114 CD0432pax 0 0.3628 0.5607 0.2532 0.0282 2.0485 0.4407 CD0437pax 0 −0.8872 −0.1793 −0.6918 −0.7768 0.4635 −0.1593 CD0472pax 0 −2.1022 −0.4543 −1.0718 −0.6968 0.0235 −0.4243 CD0482pax 0 3.2778 3.4857 2.2282 2.2532 4.6085 3.4507 CD0484pax 0 0.2778 1.1907 0.3932 1.3182 1.7635 0.4107 CD0507pax 0 1.4228 1.0757 1.0982 0.4282 2.4985 1.5357 CD0547pax 0 −1.6622 −0.1543 −0.5068 0.0632 0.1035 −0.3643 CD0571pax 0 0.9378 1.2407 1.0382 1.8282 2.3535 0.5757 CD0580pax 0 1.2978 1.6557 0.5582 0.4382 2.3585 1.2807 CD0583pax 0 −0.4472 −0.9493 −0.4968 −0.5218 0.7935 −0.6093 CD0603pax 0 0.6928 0.5507 0.1582 −0.0818 1.4135 1.2457 CD0604pax 0 0.0028 0.6557 −0.1218 −0.1268 1.6635 −0.1443 CD0619pax 0 −0.3072 0.2557 0.1532 0.5182 0.3285 0.8407 CD0637pax 0 0.3428 0.0357 −0.0618 0.3132 0.8935 0.6657 CD0667pax 0 −0.5672 −0.4993 −0.5168 −0.1568 0.0235 −0.2643 CD0670pax 0 3.0478 2.9307 1.7582 1.5882 3.3985 2.6957 CD0676pax 0 −0.7022 −0.6343 −0.5518 −1.0468 0.2485 0.0357 CD0687pax 0 1.4528 2.5807 1.6032 1.9382 1.9035 2.4357 CD0715pax 0 −2.1372 −1.5893 −1.0468 −0.7768 −0.3665 0.4757 CD0721pax 0 0.1778 1.1807 0.0382 0.0582 1.1935 0.7607 CD0726pax 0 −0.2472 −0.2193 0.0432 −0.0318 0.8985 −1.1393 CD0743pax 0 0.4178 −0.4243 0.2032 0.2782 1.6735 −0.0243 CD0786pax 0 0.6678 1.0807 0.6132 0.9682 1.8735 1.0607 CD0800pax 0 2.6478 2.7757 1.9282 2.4682 3.8585 3.0107 CD0829pax 0 −0.0722 0.4757 0.2082 −0.3318 0.5785 0.7957 CD0833pax 0 0.1378 −0.3693 0.0982 0.5032 0.8185 −0.2293 CD0840pax 0 −0.5072 0.4157 −0.2018 −0.5618 0.6035 0.1307 CD0843pax 0 0.2853 −0.1433 −0.2192 −0.5291 0.3415 0.2136 CD0937pax 0 1.2178 0.8507 0.9632 1.4432 2.6285 1.8457 CD1001pax 0 0.7553 0.8367 0.2758 −0.3541 2.7865 0.9686 CD1032pax 0 −3.0422 −2.3193 −0.7918 −0.7218 −1.1065 0.0557 CD1068pax 0 −0.1722 −0.0343 0.1382 0.5532 2.0935 −0.2243 CD1134pax 0 0.4253 1.2867 0.2608 0.4409 1.3565 1.9236 CD1269pax 0 0.0378 1.3507 0.1732 −0.2218 1.1735 1.1007 CD1270pax 0 0.8328 0.8557 0.6482 0.3532 1.4535 1.4157 CD1271pax 0 1.6778 2.4257 1.2282 0.6282 0.9885 1.8207 CD1278pax 0 0.2578 1.0757 0.5232 0.1582 1.2685 1.3507 CD1285pax 0 0.6903 0.3917 0.8458 0.3609 2.7765 0.8986 CD1313pax 0 1.7278 1.3757 0.8182 1.0282 2.8285 0.6057 CD1320pax 0 −0.8972 0.2757 −0.6068 −0.0668 0.1335 0.7907 CD1329pax 0 0.1903 −0.0983 0.2308 −0.3091 1.1115 0.8936 CD1349pax 0 −0.1622 0.5757 −0.3668 −0.9268 0.3935 0.5807 CD1401pax 0 −0.0397 −0.2933 −0.2492 0.2409 0.2715 0.2036 CD1428pax 0 2.0228 2.1257 1.1632 2.0382 2.5385 1.4807 CD1438pax 0 −0.1572 0.3757 −0.1418 0.3782 0.6935 −0.1493 CD1441pax 0 −0.6972 0.3307 0.0582 0.1132 0.7235 −0.3693 CD1458pax 0 0.2328 0.2407 0.9082 0.7332 1.8935 0.5707 CD1487pax 0 0.2378 1.9757 0.9582 1.6032 1.9785 0.5407 CD1559pax 0 −0.0022 0.8557 0.1632 0.3532 1.8685 1.0657 CD1561pax 0 1.1728 0.7557 0.6132 0.5432 1.8635 1.9307 CD1567pax 0 0.6928 1.4807 0.4982 1.2232 1.6035 1.2807 CD1627pax 0 −1.0072 −0.6693 −0.1868 0.2632 −0.4965 −0.2743 CD1708pax 0 1.3903 1.8417 1.1458 0.6909 2.4365 1.8636 CD1719pax 0 −0.4022 0.0407 −0.3068 −0.7568 0.1285 0.4657 CD1728pax 0 1.8578 2.0957 1.2732 2.0332 1.9635 3.0907 CD1741pax 0 −0.4922 −0.5493 −0.1868 −0.4618 1.0035 0.3257 PB0662pax 0 0.0003 0.3867 0.6908 0.6809 1.2815 −0.1464 PB0701pax 0 0.8803 1.5017 1.2058 2.1159 1.6765 3.1036 PB0790pax 0 0.4253 0.2867 0.5158 0.5459 0.1665 −0.2414 PB1222pax 0 −0.0272 0.4407 0.2932 −0.6868 −0.0465 0.8957 PB1260pax 0 −1.3447 −1.3983 −0.3742 −1.2441 −0.6585 −0.5814 PB1275pax 0 −0.7447 0.3767 −0.3092 0.2359 −Q.1835 2.1786 PB1324pax 0 −0.1597 0.5667 0.4508 1.1109 1.7015 1.8886 PB1336pax 0 0.4853 0.6817 0.2158 −0.5991 1.1365 1.5136 PB1446pax 0 −0.9897 −0.0133 −0.1992 0.0159 0.7765 1.0086 PB1514pax 0 −1.2222 −0.2093 −0.3418 −0.4868 0.8185 −0.0293 PB1540pax 0 −0.7672 −0.2493 −0.2668 −0.0068 0.5185 0.8157 PB1700pax 0 0.5403 0.7517 0.5258 0.8759 1.3265 0.8836 PB1763pax 0 2.0953 2.5067 1.7958 2.6409 3.0115 1.9736 PB1785pax 0 0.9903 1.6717 0.6008 1.4309 1.3415 0.9486 PB1871pax 0 0.4853 0.3717 0.2008 0.3059 1.3365 1.4286 PB1918pax 0 2.6678 2.3457 1.4632 1.7882 3.8835 2.6107 PB1944pax 0 0.0028 −0.4843 0.4432 0.7482 0.5435 1.3507 PB1952pax 0 1.9703 1.9167 0.5508 1.8859 2.9865 2.0386 PB1973pax 0 2.7753 2.8667 1.9308 3.1009 3.7065 3.7736 PB1984pax 0 −2.2397 −1.7683 −1.8492 −1.7341 −1.4835 −1.3114 PB2005pax 0 1.4803 1.5917 0.8408 1.1159 3.3915 1.8386 PB2015pax 0 2.4703 1.9567 2.0908 3.2409 4.2865 2.5086 PB2024pax 0 0.8053 1.3967 0.8908 1.1359 2.6515 2.2286 PB2041pax 0 −0.5647 0.7517 −0.0692 0.1909 1.7565 0.1836 PB2062pax 0 2.4703 2.4517 1.7908 2.2809 3.3065 2.6786 PB2084pax 0 1.3553 1.0517 0.6808 1.5959 2.3965 1.4886 PB2130pax 0 0.4353 0.6717 0.0408 −0.1091 0.6315 0.6436 PB2179pax 0 0.6453 1.5017 0.5358 0.3559 0.7115 0.8686 PB2184pax 0 −0.8047 −0.1983 −0.3292 0.0859 0.2715 1.4886 PB2258pax 0 −0.0397 −0.9183 −0.5042 −0.4191 0.8415 −1.1164 PB2272pax 0 2.2653 2.2717 1.6408 1.7259 4.0015 1.8136 PB2342pax 0 2.9678 2.7557 1.1682 1.6732 2.4335 2.7607 PB2464pax 0 1.0003 1.6717 0.8458 0.4759 1.4465 3.2686 PB2516pax 0 0.1603 0.8067 0.4858 0.2109 0.6065 1.9036 PB2564pax 0 0.1253 1.3217 0.0258 0.3009 0.5815 0.7836 PB2634pax 0 0.0153 1.1567 0.8958 0.7009 2.5465 0.5586 PB2682pax 0 −1.2297 −0.1383 −0.5242 −1.4441 0.0415 −0.0114 PB2709pax 0 1.2978 1.7457 1.3832 1.9982 2.2535 1.3107 PB2711pax 0 −0.8797 −1.1033 −0.3892 −0.8391 0.5215 0.4736 PB2757pax 0 0.5353 1.6117 0.8508 0.6659 1.5865 1.9836 PB2809pax 0 −0.1722 0.9957 0.0032 −0.1768 0.6335 0.9057 PB2842pax 0 −0.5547 0.3867 −0.3492 0.0209 −0.2585 0.3486 PB2875pax 0 −0.0497 1.2967 0.3958 0.3959 1.2365 1.1736 PB2889pax 0 0.6453 1.9717 1.0808 1.4209 1.4015 1.5286 PB2909pax 0 −0.1372 −1.0543 −0.4368 −0.7268 0.2735 −0.3993 PB2924pax 0 0.7803 1.5167 1.1858 1.2159 1.3115 1.2786 PB2927pax 0 2.1453 0.8717 0.7158 0.1309 1.5815 2.1286 PB2931pax 0 0.2203 −0.3283 −0.8242 −0.8241 1.8315 −0.3664 PB2951pax 0 −0.0897 −1.6683 −1.0792 −0.2891 −0.3035 −0.9164 PB2974pax 0 −0.2547 0.8417 0.1958 0.2259 1.0515 2.2086 PB2978pax 0 3.1253 3.2667 2.2458 2.4059 3.7165 2.9886 PB2988pax 0 −1.5847 −1.3333 −0.7892 −1.1941 −0.2435 −0.3764 PB3014pax 0 1.3953 1.9017 1.2458 0.7959 2.3615 2.5236 PB3021pax 0 0.3053 2.1667 0.4108 0.9459 0.9015 0.7786 PB3032pax 0 −0.1547 0.4867 0.6658 0.0409 1.5065 1.1036 PB3163pax 0 0.3003 1.4117 0.5908 1.1459 2.4115 1.7336 PB3193pax 0 −0.0047 0.3717 0.0058 0.4559 1.1065 0.7036 PB3200pax 0 0.2653 1.0967 0.8608 1.0859 1.4265 1.5786 PB3226pax 0 0.3203 0.9467 0.4658 0.6709 1.9165 1.1536 PB3227pax 0 −0.0147 0.7317 0.4658 0.6559 2.0115 1.3936 PB3361pax 0 −0.8197 −0.1133 −0.5592 −0.9891 0.8715 −0.6564 PB3439pax 0 −1.2272 −1.8643 −1.1768 −1.2568 −0.9015 −1.7543 PB3445pax 0 1.6203 2.4017 1.5208 2.2859 2.7265 2.2836 PB3481pax 0 −0.0397 0.9167 0.3308 1.1359 0.5015 1.3636 PB3513pax 0 −0.0347 −0.2133 −0.5142 −0.6891 0.8765 −0.9214 PB3524pax 0 0.2103 −0.5733 0.1758 0.1859 1.2865 0.8486 PB3533pax 0 −0.3047 −0.7483 −0.2442 −0.0641 1.0465 −0.2664 PB3568pax 0 1.3153 1.4267 0.9858 1.0159 1.8915 0.8386 PB3582pax 0 1.4703 2.3517 1.7258 1.8509 3.3165 2.4236 PB3594pax 0 1.0753 1.2267 0.6958 1.2059 2.4615 1.2786 PB3806pax 0 −1.7122 0.1507 −0.6168 −0.1418 −0.2615 −0.3843 PB3828pax 0 −0.8197 0.3417 −0.2942 −0.6091 −0.2085 0.4136 PB3863pax 0 1.9153 1.8567 1.5808 1.4659 2.7065 2.5436 PB3877pax 0 2.1003 2.3217 1.6458 1.3909 3.4115 2.2186 RC2112pax 0 1.0653 2.1567 1.3008 1.7109 1.6115 2.0886 RC2236pax 0 1.1903 1.2017 1.0508 1.2159 1.5165 2.2136 RC2239pax 0 −0.2897 1.0767 1.0608 1.3759 0.5315 1.6386 RC2252pax 0 2.5353 1.9417 1.4658 1.9359 1.9515 2.7336 RC2338pax 0 1.1953 2.1167 1.1358 1.0609 2.2215 2.0636 RC2565pax 0 0.0753 1.1417 0.0458 1.2659 0.5465 2.0486 RC2615pax 0 −0.4847 0.1417 0.3558 0.5509 0.2765 1.1436 RC2699pax 0 1.1453 1.5167 0.8658 0.6759 1.7615 1.5636 RC2716pax 0 0.2703 0.4317 0.7308 1.1609 2.2865 0.9336 RC2728pax 0 −0.1697 1.2267 0.8108 0.5209 1.1265 0.4386 RC2768pax 0 1.2553 1.6867 0.9908 1.5259 1.8865 2.7936 RC2782pax 0 2.7703 3.4667 2.2058 2.3409 5.0215 2.7836 RC2869pax 0 1.3178 1.1907 0.7582 1.3432 2.3085 2.1657 RC2897pax 0 0.1853 0.7067 −0.0642 0.3409 1.1865 1.0436 RC2986pax 0 0.8953 0.9867 0.3458 0.4359 2.5115 1.4186 RC3191pax 0 1.4403 2.2267 1.2558 1.0409 1.9615 2.2036 RC3214pax 0 0.7903 1.6817 0.8258 0.8409 2.5365 1.1586 RC3379pax 0 1.3003 1.7467 1.0158 1.0509 2.4615 0.5686 RC3420pax 0 0.9153 1.0217 0.9258 1.6209 2.5815 0.4436 AN0001pax 1 −2.1122 −1.1143 −1.0218 −1.6018 −0.1515 −0.4493 AN0003pax 1 −3.9172 −2.1693 −2.9568 −1.2268 −2.2065 −2.5393 AN0007pax 1 −3.0572 −1.7593 −2.1818 −3.1218 −2.5615 −1.0493 AN0009pax 1 −0.3772 0.6607 0.0832 −0.0718 1.9985 1.0707 AN0012pax 1 0.5478 1.1207 0.3632 −0.0868 1.6385 1.6507 AN0013pax 1 0.2178 2.0007 0.9732 0.1332 2.7685 2.1157 AN0020pax 1 −1.8472 −0.4843 −1.1768 −1.7718 −1.3165 −0.3293 AN4011pax 1 −0.0972 0.8507 0.9782 0.5082 2.1785 0.9257 AN4012pax 1 1.6828 1.2857 1.1782 1.2582 2.7935 2.4957 AN4013pax 1 0.7928 2.0057 0.8132 0.6482 1.6385 1.8907 AN4014pax 1 −1.0472 0.2207 −0.1918 0.1232 0.4685 1.9757 AN4017pax 1 1.0003 1.3817 0.3358 0.2709 0.4565 1.2836 BE3001pax 1 −1.4472 0.2507 −0.3068 −0.6768 −0.8115 0.8657 CC0001pax 1 −0.2222 0.1107 −0.1668 −0.0168 1.2635 0.7907 CC0002pax 1 −0.5572 −0.8993 −0.6118 −1.9568 −0.2715 0.0957 CC0004pax 1 −1.2622 −1.0993 −0.4268 −0.1268 0.5335 0.6457 CC0005pax 1 0.8628 1.2457 0.6532 0.9132 1.8285 0.4607 CC0006pax 1 0.3128 0.4957 0.2332 0.5682 1.7235 2.2507 CC0007pax 1 −1.5122 0.0857 −0.2318 0.0032 −0.1365 0.3407 CC2001pax 1 −0.6672 1.0957 −0.0268 0.1382 0.9435 0.7757 CC2002pax 1 −0.6022 −0.9543 −0.6518 −1.5068 −0.2315 −0.3993 CD1111pax 1 1.5528 0.9857 1.1082 1.6382 2.0285 2.2057 CD1260pax 1 −0.4922 −0.5393 0.0532 −0.5368 1.1035 0.7257 CD1351pax 1 0.3978 0.4007 −0.0268 −0.3368 1.6485 0.5707 CD1571pax 1 0.6253 0.7717 0.9908 1.7909 2.5465 1.3386 CD1690pax 1 0.4278 0.5007 0.4682 0.5232 1.3985 −0.1993 DC0003pax 1 0.3378 0.8707 0.1182 0.0432 0.8135 1.8807 DC0005pax 1 0.6328 1.6957 0.6782 0.4432 1.5635 1.7007 DC0008pax 1 0.3628 0.7757 0.4632 −0.3718 1.6735 0.2907 DC0011pax 1 −0.1322 0.4157 0.5532 0.5082 1.5035 1.6757 DC0012pax 1 −1.2222 −0.4443 −0.6868 0.3132 −1.1115 −0.2343 DC1002pax 1 −1.2322 −0.7593 −0.3968 −0.3968 0.5535 0.3907 DC2005pax 1 −2.3922 −1.8993 −1.9468 −0.6968 −1.5515 −0.4343 DC2006pax 1 0.1778 0.4107 0.1982 −0.6518 1.0185 0.8557 DC3003pax 1 −0.2272 0.9507 0.1682 −0.4168 1.5985 1.8207 DC5006Apax 1 −0.0922 0.2057 0.2232 −0.3768 −0.1115 0.2157 DC5008Apax 1 −0.5972 −0.1043 −0.7018 −0.5168 0.8335 1.1557 DES1001pax 1 −1.8422 −0.8843 −1.1918 −1.4518 0.8185 −0.4143 DES1002pax 1 −0.6822 −0.8993 −0.0418 −0.5318 1.1235 −0.7943 JH0022pax 1 0.0828 0.5507 0.4282 0.5332 0.5935 1.0307 JH0076pax 1 −0.4872 −0.7793 −0.2418 −1.6768 −0.1715 0.1407 JH0085pax 1 −1.0822 −0.6293 −0.4668 −1.2268 −0.0365 −0.0193 JH0089pax 1 −0.1597 1.0267 −0.1642 −0.5691 0.7915 1.1336 JH0090pax 1 −0.7322 −1.0293 −0.4218 −0.0518 0.0435 0.4657 JH0091pax 1 0.1353 0.2617 0.2708 1.2709 1.2965 1.1536 JH0093pax 1 0.2428 1.4557 0.4232 −0.5368 1.5685 0.9107 JH0096pax 1 −2.0347 −0.6183 −1.4842 −0.6891 −2.2235 0.8736 JH0097pax 1 −0.4422 −0.5293 −0.0218 −0.7968 0.4985 −0.7193 JH0100pax 1 0.3803 1.2117 0.4858 0.6959 1.7015 1.0036 JH0101pax 1 0.8128 0.4507 0.6232 0.3482 1.6835 0.5857 JH0105pax 1 0.3878 1.1657 0.3682 −0.5768 1.7485 2.0007 JH0106pax 1 −0.6497 −0.2083 0.0308 −0.1191 0.8115 1.1536 JH0108pax 1 −0.0772 0.6557 0.3282 −0.0768 0.8485 1.1157 JH0109pax 1 0.9803 1.9517 0.7158 0.2559 1.7615 2.2986 JH0110pax 1 −0.5072 0.2307 −0.1668 −0.6018 −0.3515 0.7807 JH0111pax 1 0.7503 1.7717 0.4808 1.8809 2.4715 1.1486 JH0113pax 1 −0.3047 0.5867 0.3308 −0.8441 0.5715 0.1886 JH0114pax 1 −2.0472 −1.6493 −1.3618 −0.6518 −1.7715 −2.1743 JH0116pax 1 −0.2772 1.1207 0.2182 0.6082 0.7885 0.7457 JH0117pax 1 −1.6972 −0.6243 −1.0418 −0.8018 −0.1765 0.4257 JH0118pax 1 0.3503 −0.0433 0.5258 −0.0441 1.1065 0.4236 JH0120pax 1 −0.3797 0.2467 −0.0792 −1.2341 1.4265 0.0686 JH0123pax 1 −1.8597 −0.9733 −0.7492 −0.5891 −0.8185 −1.2464 JH0126pax 1 −1.7822 −0.3243 −0.7168 −1.3618 −0.6665 0.2307 JH0127pax 1 −0.3897 1.0367 0.4308 0.7759 0.6415 0.6086 JH0129pax 1 0.3903 1.2817 0.6808 1.0259 2.6865 1.8886 JH0130pax 1 −0.9022 −0.3543 −0.7818 −0.9818 −0.4465 0.2657 JH0131pax 1 −0.4922 −0.5243 −0.5968 −1.3968 −0.8715 0.2057 JH0132pax 1 −0.3897 0.1117 −0.0742 0.3959 0.4615 0.1436 JH0135pax 1 −1.3622 −1.6143 −1.2368 −1.1018 −1.2465 −1.4743 JH0136pax 1 −2.6172 −1.9043 −1.3118 −1.4768 −1.1965 −2.0743 JH0137pax 1 −0.1372 0.9407 −0.3768 −0.6168 0.7685 0.5507 JH0138pax 1 −0.5622 0.1957 0.0532 −0.3068 0.2285 0.2757 JH0139pax 1 −0.7247 −0.6583 −0.5792 −1.1191 −0.4935 −0.8464 JH0142pax 1 −0.4547 0.7017 0.3608 0.4459 0.7815 −0.1964 JH0144pax 1 0.3128 2.3157 0.8682 −0.1368 2.0135 1.2707 JH0147pax 1 0.3778 1.4257 0.4532 0.5232 2.9535 0.7407 JH0149pax 1 0.5528 1.2407 0.3682 0.1432 2.5535 0.9357 KW0002pax 1 −0.4072 0.4307 −0.1868 −0.4968 0.6785 1.3907 KW0003pax 1 0.0253 1.3217 0.7908 −0.0691 0.1415 3.0886 MH0053pax 1 2.2253 2.3967 1.2558 0.6209 3.2815 2.1886 MH0057pax 1 −0.6947 −0.5333 −0.4792 −0.5041 0.5915 −0.5264 MH0059pax 1 −2.8497 −2.1083 −2.1892 −1.5691 −0.3235 −1.1764 MH0062pax 1 −0.9697 −0.1633 −0.0592 −0.4891 0.5065 0.3186 MH0065pax 1 −1.7097 −1.6233 −0.8042 −0.9491 −0.6235 −1.1314 MH0066pax 1 −1.4297 −0.9733 −1.0642 −0.8041 −0.5235 −0.9314 MH0068pax 1 2.4828 2.4407 1.7882 1.6982 3.0035 1.0707 MH0070pax 1 0.1703 0.8467 0.5808 0.3859 1.4015 1.1036 MH0073pax 1 −1.5622 −0.8493 −1.3868 −1.4018 −0.1715 −0.7993 MH0074pax 1 −1.0422 −1.1393 −0.6218 −0.6218 0.7535 −1.2193 MH0076pax 1 0.2653 1.8167 0.0658 −0.4241 2.0165 2.0386 MH0077pax 1 −0.2772 0.3357 −0.2418 −0.6218 0.2935 0.4157 MH0078pax 1 −1.2497 −0.0583 −0.6992 −1.7091 −0.7685 1.0236 MH0079pax 1 0.6153 0.7767 0.5608 −0.0241 0.6065 1.1786 MH0080pax 1 −0.1597 0.2867 0.5258 0.3709 1.5765 0.6186 MH0081pax 1 0.1403 1.2367 0.1658 −1.1941 1.7615 0.7686 MH0082pax 1 0.8203 1.4817 0.4558 −0.1441 1.6365 0.7336 MH0083pax 1 1.5778 1.7007 0.9332 1.2532 2.2185 1.6807 MH0087pax 1 −0.9922 0.9707 −0.0668 0.5032 1.4985 0.6507 MH0088pax 1 −0.2172 0.8457 0.3582 −0.1868 0.8535 0.5157 MH0089pax 1 −2.2197 −1.5133 −1.0292 −1.5141 −0.8685 −0.3364 MH0090pax 1 −0.9247 0.3217 −0.2792 −0.6841 0.0065 −0.4964 MH0095pax 1 −2.1147 −1.5633 −1.4142 −1.8041 −1.0985 −0.9514 MIP0002pax 1 −1.8047 −0.3533 −0.6842 −0.1141 −0.0685 0.4836 MIP0003pax 1 0.0778 0.1157 −0.1818 0.0282 0.7585 −0.1643 MIP0005pax 1 −2.2797 −1.3883 −1.6292 −1.1741 −0.8035 −1.7414 MIP0008pax 1 0.5053 0.8367 0.0008 −0.2191 1.8415 0.7086 MIP0009pax 1 −1.3122 −1.1793 −1.2268 −1.4768 −0.6215 −1.0043 MIP1007pax 1 −1.1547 −0.4633 −0.4792 0.1859 0.2515 −1.4864 MIP1009pax 1 −2.9997 −1.6083 −2.0442 −1.4391 −0.7485 −1.1164 MIP1011pax 1 −0.6497 −0.7283 −0.8992 −1.0491 0.3015 −0.8914 MIP1013pax 1 −0.0222 0.8707 0.0282 0.0432 0.7335 1.4007 MIP2002pax 1 0.8603 1.4317 0.7358 0.4159 1.6165 1.3386 MIP2003pax 1 −0.2947 0.3567 0.2508 0.6959 1.8515 0.8486 MIP2006pax 1 −0.3622 0.7457 0.0432 0.5432 0.8035 0.3157 MIP3003pax 1 −2.5772 −1.5843 −2.1418 −1.4368 −1.7415 −1.3193 MIP3004pax 1 −0.9222 −0.5393 −0.4618 −0.3918 0.6435 −0.6943 NK1001pax 1 0.4828 1.0657 0.0782 0.1832 1.9635 0.9307 NK1003pax 1 −0.9747 0.1017 −0.1192 −0.3691 0.4365 0.4536 NK1004pax 1 −0.7947 −0.5133 −0.4642 −0.8441 0.6715 0.0186 NK1005pax 1 −0.1597 1.5217 0.8058 0.4809 2.0815 0.9936 NK1008pax 1 −1.6222 0.1407 −0.5918 −0.2818 −0.0215 0.2257 NK1009pax 1 1.6828 1.5207 0.7182 0.4582 2.3135 1.0907 NK2005pax 1 −1.5347 −0.9483 −0.6192 −0.8041 −1.9435 −0.0114 NK2006pax 1 −1.9272 −1.2543 −1.7168 −1.1568 −0.7815 −1.6093 NK2007pax 1 0.1978 0.4957 0.1282 0.6782 1.0285 −0.0693 NK2008pax 1 −1.9022 −1.2193 −1.0068 −1.3468 −0.0615 −1.4393 NK2009pax 1 −0.4097 0.3167 0.0658 −0.7691 1.5165 −0.0614 NK2010pax 1 −1.1147 −0.5983 −0.4692 −0.8091 −0.3935 −0.7364 NK2014pax 1 0.6753 1.6317 1.0258 1.0759 2.0515 1.1686 NK2015pax 1 −0.6222 0.6307 0.0482 −0.4318 1.6935 1.3107 NK2016pax 1 −0.4297 0.2167 −0.2092 0.0659 1.6815 0.4936 NK2018pax 1 −1.9522 −1.1093 −0.8468 −0.9018 −0.2715 −0.9843 NK5008pax 1 −1.4522 −1.6693 −1.3418 −1.5618 0.4085 −1.2843 OL0003pax 1 −1.2897 −0.5083 −0.9542 −0.7241 −0.1385 −0.3214 OL0014pax 1 −2.3397 −2.4483 −1.7342 −1.7191 −1.8585 −1.0564 OL0017pax 1 −1.0297 −1.0083 −0.6692 −0.5541 0.6465 0.3036 OL0026pax 1 −2.2947 −1.4533 −2.0092 −1.8291 −0.6635 −0.4364 OL0034pax 1 −1.3647 −0.8333 −1.2992 −1.7341 0.1615 0.0536 OL0041pax 1 −2.2297 −1.6183 −2.1492 −2.8641 −1.4835 −2.1464 OL0043pax 1 −0.8772 −0.6193 −0.7268 −1.2568 0.0285 −0.5693 OL0052pax 1 −1.3047 −1.2733 −0.4242 −0.5541 −0.2135 −0.5464 OL0056pax 1 −0.2972 −0.9943 −0.0518 −0.6268 1.5235 0.6557 OL0057pax 1 −0.8447 −0.4883 −0.7942 −0.8191 −0.1335 −0.1664 OL0058pax 1 −1.1572 −1.2643 −1.1518 −0.9918 −0.1265 −1.8993 OL0059pax 1 −1.1947 −0.0983 −0.5492 0.0109 0.0115 0.0936 OL0060pax 1 −1.8622 −1.6843 −1.4368 −2.0668 −1.6665 −1.0693 OL0062pax 1 0.3003 0.2817 0.3108 0.0709 1.7915 1.3986 OL0063pax 1 −1.3172 −0.8843 −0.8068 −0.5168 −0.3665 −0.7093 OL0064pax 1 0.3203 0.9317 0.7908 0.6409 1.8015 0.7186 OL0065pax 1 0.4578 0.7257 0.6832 0.6982 1.8085 0.6357 OL0066pax 1 −0.2722 0.5757 −0.0618 0.4232 0.6785 1.0357 OL0068pax 1 −1.9622 −0.7143 −1.3218 −1.1918 −0.5765 −1.0593 OL0070pax 1 −1.3622 −0.6193 −1.2868 −2.0718 −0.3665 −1.5243 OL0071pax 1 −0.6897 0.1217 −0.3542 0.1559 0.7515 0.8136 OL0072pax 1 −1.1047 −0.4033 −0.4392 −1.1791 0.2315 −0.9964 OL0073pax 1 −2.6897 −1.9933 −1.1642 −1.1641 0.3565 −0.5114 OL0074pax 1 −1.4447 −0.7883 −0.9142 −0.6891 1.0865 −0.1364 OL0075pax 1 −0.8322 −0.0343 −0.3218 0.3782 0.8585 0.5457 OL0077pax 1 −1.0747 −0.5933 0.1708 0.3059 0.2265 0.2036 OL0078pax 1 −2.2597 −1.8983 −1.1942 −1.1441 −0.8135 −0.9764 OL0079pax 1 −1.1797 −0.7633 −0.9442 −1.2641 −0.8335 −0.0214 OL0080pax 1 −0.0772 0.4507 0.2882 0.3882 0.3985 0.5357 PB3545pax 1 −0.3222 1.4657 0.0382 0.4682 1.1435 0.6807 PB3890pax 1 −0.4397 −0.2383 0.4108 0.7759 0.1265 0.1686

The test set results confirmed the surprising finding based on the training set that ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 each express RNA on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 13). The ranges of fold-change in the levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of the test set subjects having colorectal cancer relative to the test set subjects not having any colorectal pathology are also shown in Table 13.

TABLE 13 Sample test set ranges of fold-changes in levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized RNA level in −0.63 0.01 −0.27 −0.38 0.56 0.28 subjects having colorectal cancer (ΔCt) Average normalized RNA level in 0.45 0.85 0.45 0.59 1.47 1.04 subjects not having any colorectal pathology (ΔCt) Average RNA level fold-change 2.11 1.80 1.65 1.95 1.88 1.69 p-value for average RNA level fold- 1.2E−17 7.3E−12 1.5E−15 2.5E−19 5.4E−12 2.6E−10 change Maximum observed RNA level 20.61 9.85 10.64 13.07 16.37 11.93 directional fold-change

As can be seen in Table 13, a test subject having a blood level of RNA encoded by ANXA3, normalized to a level of RNA encoded by IL2RB, which is 2.1 to 20.6 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 13, a test subject having a blood level of RNA encoded by CLEC4D, normalized to a level of RNA encoded by IL2RB, which is 1.8 to 9.85 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 13, a test subject having a blood level of RNA encoded by LMNB1, normalized to a level of RNA encoded by IL2RB, which is 1.65 to 10.6 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 13, a test subject having a blood level of RNA encoded by PRRG4, normalized to a level of RNA encoded by IL2RB, which is 1.95 to 13.1 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 13, a test subject having a blood level of RNA encoded by TNFAIP6, normalized to a level of RNA encoded by IL2RB, which is 1.9 to 16.4 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 13, a test subject having a blood level of RNA encoded by VNN1, normalized to a level of RNA encoded by IL2RB, which is 1.7 to 11.9 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Furthermore, the test set results confirmed the surprising finding based on the training set that logistic regression models based on blood expression levels for any of the 63 possible combinations of one or more of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, each of which normalized against expression levels of IL2RB, can be used to discriminate, with a ROC AUC of at least 0.66 (Table 11), between subjects having colorectal cancer and subjects not having any colorectal pathology. As such, the novel logistic regression models listed in Table 11 can be used to determine the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, based on blood levels of expression of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and/or VNN1 normalized to those of IL2RB.

Example 4 Determination of the Probability that a Test Subject has Colorectal Cancer as Opposed to not Having Colorectal Cancer Using Blood Levels of RNA Encoded by the Colorectal Cancer Markers: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 Normalized to those of ACTB

A blood sample from a test subject is analyzed for levels of RNA encoded by ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, as described in Example 1, above, thereby generating test data. Logistic regression model #1 of Table 6 is applied to the test data, thereby providing the probability that the test subject has colorectal cancer as opposed to not having any colorectal pathology.

Example 5 Determination of the Probability that a Test Subject has Colorectal Cancer as Opposed to not Having Colorectal Cancer Using Blood Levels of RNA Encoded by the Colorectal Cancer Markers: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 Normalized to those of IL2RB

A blood sample from a test subject is analyzed for levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 as described in Example 1, above, thereby generating test data. Logistic regression model #64 of Table 11 is applied to the test data, thereby providing the probability that the test subject has colorectal cancer as opposed to not having any colorectal pathology.

Example 6 Measurement of Blood Levels of RNA Encoded by a Combination of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 Relative to the Level of RNA Encoded by IL2RB can be Used to Determine the Probability that a Test Subject has Colorectal Cancer as Opposed to not Having any Colorectal Pathology

Materials and Methods:

Refer to “General materials and methods”, above.

Experimental Results:

Sample Training Set:

Discovery of significantly different levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, VNN1, TNFAIP6 normalized to IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology: Quantitative reverse transcriptase-PCR analysis of gene expression in a training set of blood samples from 112 subjects having colorectal cancer and 120 subjects not having any colorectal pathology (subset of samples listed in Table 9 of Example 3, above), using IL2RB as duplex partner for normalization of gene expression levels was performed. The normalized RNA levels measured are shown in Table 14.

TABLE 14 Sample training set levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by IL2RB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 CD0011pax 0 1.0600 1.5250 1.3250 1.1000 2.3500 2.7750 CD0012pax 0 1.3600 1.6300 0.8600 0.8500 1.8350 2.7300 CD0030pax 0 1.4100 1.4500 0.9800 1.2850 1.0250 1.9600 CD0063pax 0 2.5700 3.3050 1.7550 1.9950 3.6000 3.2500 CD0077pax 0 −0.2350 0.7700 0.1500 0.3000 0.3900 1.1650 CD0078pax 0 1.5150 2.2800 0.7550 0.6750 2.6250 1.3750 CD0085pax 0 0.5750 1.6050 0.6450 0.9450 2.5450 0.7200 CD0117pax 0 0.9750 2.3900 0.9250 2.0600 2.4600 0.9400 CD0167pax 0 −0.9750 0.2000 0.4600 0.6600 1.6250 0.5800 CD0249pax 0 −0.5100 −0.2750 −0.5200 0.3200 0.2750 0.6400 CD0286pax 0 −0.2850 1.0900 0.2500 0.2050 0.3550 0.3300 CD0297pax 0 0.0300 0.4850 0.4700 −0.0300 0.3900 1.0050 CD0323pax 0 1.9000 1.9500 0.8350 1.4850 2.6400 3.4450 CD0445pax 0 0.6600 0.8250 0.3000 0.3750 1.4100 1.4350 CD0463pax 0 −0.0850 1.7650 0.6000 0.8550 1.3700 1.5650 CD0491pax 0 −0.5550 0.0650 0.1100 0.5450 0.9000 0.2150 CD0496pax 0 1.2050 2.8450 1.2400 1.9200 1.4650 1.3450 CD0501pax 0 1.1050 1.9100 1.1100 1.0600 2.8650 1.4900 CD0504pax 0 −0.7750 −0.2850 −0.1500 0.6100 −0.1950 0.3350 CD0573pax 0 1.8100 1.2350 0.7700 0.8300 2.2650 1.8500 CD0578pax 0 1.8200 1.9800 0.9550 1.0450 2.0700 2.2950 CD0639pax 0 0.2950 0.7900 0.7450 −0.2600 1.2000 1.7900 CD0645pax 0 −1.0950 −0.6000 −0.7700 −0.6250 −0.0200 −0.1800 CD0679pax 0 0.2300 1.5950 0.5200 0.3350 1.8800 1.8750 CD0685pax 0 0.5250 1.7300 0.4350 0.9850 1.6850 1.0550 CD0716pax 0 1.9900 2.4700 0.8200 0.5250 1.4050 2.1600 CD0749pax 0 0.1600 1.0600 0.1200 0.3600 1.6800 0.8350 CD0760pax 0 −2.3750 −1.0500 −1.7400 −0.9100 −0.8100 −0.6700 CD0811pax 0 1.9250 2.3300 0.7400 0.8900 0.9700 1.0100 CD0848pax 0 1.0900 1.6300 1.4050 1.3850 1.9400 2.4750 CD0924pax 0 0.3450 0.7500 0.2250 −0.1100 0.5050 0.3050 CD1066pax 0 −0.2050 0.0950 −0.1200 −0.1750 1.3650 0.1800 CD1073pax 0 0.3050 0.1350 0.3150 0.9350 1.0850 0.3400 CD1075pax 0 0.0300 0.9000 0.4100 1.5200 1.6000 0.8400 CD1089pax 0 −1.3250 −0.2000 −1.1200 −0.8700 −0.1650 −0.2550 CD1116pax 0 −0.3850 −0.3700 −0.4500 0.0001 1.0600 0.1750 CD1120pax 0 −1.1350 −0.0400 −0.7450 0.0150 1.0100 −0.5700 CD1198pax 0 0.2950 0.4300 0.6350 0.5200 0.7850 0.6000 PB1179pax 0 1.2100 1.2700 1.1550 1.2700 2.6850 1.7300 PB1277pax 0 0.6600 1.3300 0.2500 0.6650 1.6000 0.5900 PB1301pax 0 −2.1150 −1.4000 −1.3850 −1.1000 −1.2350 −1.7950 PB1315pax 0 −1.3350 0.4800 −0.3200 −0.1800 0.0600 1.0750 PB1345pax 0 0.0150 0.5500 0.5950 0.8350 0.3650 1.9650 PB1520pax 0 0.9250 2.0050 0.7850 −0.1800 1.4100 1.8550 PB1574pax 0 1.2150 2.0550 1.2150 0.9500 1.3300 1.7150 PB1783pax 0 1.7400 1.8450 1.3600 1.3450 2.3150 1.8150 PB1799pax 0 0.7800 1.1900 0.6900 1.1150 2.3400 0.9800 PB1811pax 0 1.0950 1.6200 1.1050 1.4050 1.5800 1.2650 PB1830pax 0 0.3450 0.8850 0.5650 0.2700 1.3300 2.4950 PB1833pax 0 −0.0150 0.7050 0.0700 0.3150 0.5200 1.2600 PB1843pax 0 0.8750 0.9400 0.4750 0.8500 −0.3150 1.6500 PB1851pax 0 0.2450 −0.0450 0.1250 0.1650 2.6550 1.3150 PB1919pax 0 1.3100 1.8550 0.6050 1.5350 2.0800 2.2100 PB1922pax 0 −0.1700 0.8350 −0.0700 0.8450 1.6350 0.5700 PB1924pax 0 0.0950 0.5700 −0.0750 0.2150 1.0050 1.3000 PB1937pax 0 1.5250 2.5500 1.3500 3.0050 2.7050 2.3350 PB1964pax 0 0.6950 2.7450 1.0200 1.6750 2.6250 3.0550 PB2027pax 0 0.0900 0.5100 0.3500 1.3200 1.5250 0.7550 PB2029pax 0 0.5250 1.0200 0.6150 0.4300 2.2750 1.4350 PB2073pax 0 0.6000 1.0100 0.9000 1.8550 1.7200 1.2800 PB2099pax 0 −0.1500 −0.0950 0.1350 0.3250 0.0950 0.6700 PB2100pax 0 1.2350 1.3800 0.8950 1.5600 2.3100 1.4450 PB2132pax 0 0.5100 1.2400 0.1700 0.5100 1.9950 1.4750 PB2168pax 0 1.1400 1.4600 0.6600 1.0000 2.1650 1.2450 PB2192pax 0 −0.0050 0.4950 −0.1450 −0.4800 0.8350 1.5800 PB2196pax 0 0.8850 1.7250 0.9850 1.9050 2.2550 1.1350 PB2200pax 0 0.8550 1.3850 0.2350 0.3050 0.9050 0.4400 PB2213pax 0 1.8550 2.0000 0.9300 0.5300 2.9900 1.5850 PB2224pax 0 −0.3850 0.4250 −0.1400 0.1000 1.8950 0.9750 PB2228pax 0 2.0300 2.2200 1.8000 2.0050 4.0300 3.0800 PB2229pax 0 0.0050 −0.0800 0.2000 −0.6150 0.9150 0.2550 PB2277pax 0 1.3400 1.0050 0.7550 0.3700 1.3100 1.7800 PB2297pax 0 0.2900 0.8050 −0.0900 −0.0850 0.5250 −0.2800 PB2312pax 0 1.5250 2.1700 1.6550 1.2050 2.2900 2.1700 PB2398pax 0 −0.3800 0.2250 0.0150 −0.4700 0.1050 1.4250 PB2409pax 0 0.3950 1.0600 0.4950 0.5050 1.1550 1.7350 PB2414pax 0 3.0050 2.6050 1.4550 2.3150 3.9600 2.1150 PB2467pax 0 0.4800 1.0800 0.3500 0.3600 2.1300 1.0850 PB2473pax 0 0.2350 0.8600 0.2850 0.8850 1.0100 1.5950 PB2512pax 0 0.8200 1.8950 1.1800 0.8200 2.0650 2.3750 PB2568pax 0 −0.2950 0.1900 −0.0900 0.5850 1.4750 1.1700 PB2571pax 0 0.5800 1.2800 0.7500 0.4300 2.0650 2.1050 PB2824pax 0 0.8400 1.3650 0.8000 1.3950 2.0150 1.7750 PB2880pax 0 1.2500 1.4400 0.8850 −0.0600 2.2550 1.8100 PB3088pax 0 1.3800 1.2900 0.8550 0.6050 2.9200 2.0800 RC0882pax 0 −0.0150 1.2350 0.2800 0.3700 1.7700 1.6550 RC0888pax 0 −1.0450 −0.4250 −0.3400 0.0550 0.4950 0.1900 RC0968pax 0 −0.6900 −0.4750 0.2700 1.5500 1.0250 2.3500 RC2114pax 0 −0.2000 0.9600 0.3300 0.6550 0.4550 2.0900 RC2238pax 0 1.3450 2.0600 0.8800 1.8300 2.7050 3.1100 RC2681pax 0 0.1100 0.6300 0.2200 0.2550 0.2550 0.6550 RC2703pax 0 1.8000 2.1000 1.0500 1.5250 1.4250 1.5350 RC2749pax 0 0.0900 0.7750 −0.0850 0.0500 1.2550 1.2500 RC2750pax 0 −1.5150 −1.0750 −0.9000 −0.2200 0.0700 −0.5400 RC2756pax 0 1.6800 1.3850 1.0550 1.4600 1.9450 2.5150 RC2771pax 0 −0.8450 0.4950 −0.6450 −0.4150 1.1200 1.2750 RC2790pax 0 1.0850 1.1500 0.6150 0.8950 1.3350 1.5650 RC2792pax 0 1.0100 0.6250 0.6300 1.0950 1.9150 1.3550 RC2808pax 0 0.4850 1.4600 0.2700 0.5100 0.6550 1.0150 RC2822pax 0 0.4750 0.8350 −0.0900 0.3350 2.2400 0.4750 RC2834pax 0 −0.7350 0.2100 −0.6700 1.5700 2.1300 −0.3050 RC2871pax 0 0.6150 1.1650 0.9250 1.3150 2.4200 2.2250 RC2879pax 0 −0.4050 0.2050 −0.2400 0.5300 0.5250 0.0900 RC2892pax 0 −0.1500 0.1200 −0.4050 0.2750 1.6700 0.9100 RC2895pax 0 1.8700 2.2100 1.3750 1.6500 1.5650 2.2500 RC2921pax 0 1.2850 1.4150 0.9900 1.4400 1.9950 2.0900 RC2958pax 0 0.9250 1.0000 0.2300 0.0001 0.2700 1.2250 RC3022pax 0 0.1450 −0.0150 0.1200 0.7850 1.3950 0.2450 RC3112pax 0 1.0250 1.2350 0.3150 0.2650 2.3150 0.8700 RC3146pax 0 −0.3350 −0.3450 −0.6200 0.8250 0.9650 −0.3750 RC3184pax 0 2.4850 2.8750 1.3900 1.6250 2.5600 2.3950 RC3232pax 0 −0.2550 0.7850 −0.2900 0.6900 −0.1250 2.6700 RC3324pax 0 0.3650 1.0800 0.1200 0.6100 1.5200 0.1250 RC3327pax 0 0.3600 0.0950 0.2250 −0.0500 1.4550 1.9700 RC3355pax 0 −0.1850 0.4200 −0.4950 −0.3100 1.2150 0.3400 RC3380pax 0 −0.6450 0.3950 −0.5700 −0.3000 0.4950 −0.2300 RC3413pax 0 0.2750 0.8950 0.1250 −0.3400 0.5050 2.3050 RC3421pax 0 0.3550 0.4600 0.3900 0.4400 0.1300 0.2750 RC3468pax 0 −0.3600 −0.2800 −0.4100 −0.5750 0.9000 0.0350 RC3498pax 0 −0.3150 −0.7750 −0.7050 −0.2900 0.7750 −0.1800 CC0003pax 1 −1.2200 −0.2350 −0.8100 −0.6450 1.0450 −0.6850 CD0157pax 1 1.2350 1.0300 0.7450 0.9100 2.5050 2.3600 CD0164pax 1 0.3150 0.8550 1.0100 1.2550 2.7950 1.8100 CD0256pax 1 −0.4000 0.2050 0.1950 1.0400 1.2350 0.3300 CD0322pax 1 −0.9950 −0.2450 −0.7150 −0.1400 0.6750 1.2850 CD0356pax 1 −0.4950 −0.8850 −0.4500 −0.5650 −0.1000 −0.8600 CD0371pax 1 0.2350 1.0650 0.0500 −0.1800 0.9500 −0.0100 CD0629pax 1 0.1350 0.9850 0.7900 1.4800 0.5100 1.3850 CD1050pax 1 1.1750 0.3600 0.6850 1.0250 1.7150 1.3150 DS0003pax 1 −1.6350 −0.5200 −1.1950 −0.4900 −0.0650 −0.0600 FC0005pax 1 −0.1950 −0.0950 0.0900 −0.0450 0.1950 1.4100 FC0011pax 1 −0.0650 0.1250 0.1700 0.0800 1.1250 0.4950 FC0012pax 1 −2.2350 −0.1250 −1.0650 −0.9850 −0.0150 −0.2000 JGA0001pax 1 −2.4550 −1.7500 −1.8250 −0.8650 −1.4800 −1.4400 JH0002pax 1 0.3150 0.7350 0.2850 0.1350 1.1700 0.3000 JH0003pax 1 0.0550 0.0650 −0.3850 −0.6250 −0.1450 0.7100 JH0004pax 1 −0.0550 −0.0050 −0.0250 −0.2100 1.4050 1.0300 JH0005pax 1 0.2950 1.3450 0.3700 0.4300 1.8650 1.2700 JH0006pax 1 −0.4300 0.4450 −0.0050 −0.0850 1.2650 −0.0600 JH0007pax 1 −2.4350 −1.9900 −1.3150 −0.1700 0.1250 −0.9150 JH0008pax 1 0.9050 2.5850 0.6250 1.1850 2.3350 1.0050 JH0009pax 1 −1.0700 −1.3450 −0.3350 −0.9650 −0.6700 0.1550 JH0010pax 1 −0.7650 0.0800 −0.1650 −0.0750 0.0300 −0.6650 JH0012pax 1 −0.2150 0.1900 0.1000 −0.2150 0.4400 0.6950 JH0013pax 1 −0.1200 0.3750 −0.0300 0.1150 2.2800 0.9200 JH0014pax 1 1.0050 0.8950 0.1500 −0.3400 1.6200 2.2850 JH0016pax 1 0.7850 1.1950 0.8600 0.4350 0.6450 1.0350 JH0018pax 1 −0.9850 −0.0250 −0.1450 −0.2900 0.0750 0.6250 JH0019pax 1 0.2350 0.8450 0.3600 −0.0500 0.4700 0.4850 JH0020pax 1 0.0150 1.7550 0.3850 −0.3900 0.5100 1.0550 JH0021pax 1 −1.1000 0.3250 −0.8650 −1.3850 −0.2350 −0.2400 JH0023pax 1 −0.4850 1.2250 0.3900 1.4500 1.0100 1.8450 JH0024pax 1 0.8350 2.0750 0.6950 1.0150 2.8900 2.4000 JH0025pax 1 −0.9850 −0.5650 −0.6350 −1.2100 −0.3500 0.0950 JH0026pax 1 −1.1000 0.7000 0.1500 0.1150 1.3050 1.0750 JH0027pax 1 −3.1650 −2.4400 −2.2300 −1.9300 −2.2400 −1.4900 JH0028pax 1 0.5350 1.3350 1.2450 1.0550 2.8950 1.8900 JH0029pax 1 −1.5700 −0.9750 −0.9300 −1.1200 −0.9200 0.4200 JH0031pax 1 −1.0400 −0.1700 −0.6950 −0.7700 0.0450 0.1250 JH0032pax 1 1.3700 1.6300 0.2650 0.1150 1.7300 1.7250 JH0033pax 1 −1.1900 0.5700 −0.8700 −1.0850 0.9700 −0.5100 JH0034pax 1 −0.7000 0.8150 0.2850 0.1300 1.4900 1.2200 JH0035pax 1 0.0500 1.5700 0.4400 −0.2850 2.1400 1.1050 JH0036pax 1 0.5650 0.9350 0.2450 0.0300 1.7450 0.8500 JH0038pax 1 −0.0100 1.2650 −0.0100 0.0400 1.9650 0.4500 JH0039pax 1 0.2600 0.5550 0.3050 0.8450 3.0050 −0.1900 JH0040pax 1 0.3950 0.9000 0.3650 0.2250 1.1100 0.8850 JH0041pax 1 0.3800 1.2000 −0.0650 −0.3050 1.4900 0.6150 JH0042pax 1 −2.4200 −0.9750 −1.4450 −0.8750 −1.4500 −1.6900 JH0043pax 1 −0.4900 0.3050 0.0001 −0.6800 −0.0800 0.3250 JH0046pax 1 0.2350 0.5950 0.9350 0.0450 1.0300 0.5850 JH0047pax 1 0.3250 2.0950 1.0700 1.4700 1.8200 2.4300 JH0051pax 1 −0.6850 0.2250 −0.1950 −0.8800 −0.0700 −0.1750 JH0052pax 1 −0.4500 0.5050 −0.1700 −0.6150 −0.1350 −0.2700 JH0053pax 1 −1.2800 −0.5550 −0.9600 −0.3500 −0.6500 −0.1450 JH0057pax 1 −0.0450 2.1200 0.3050 0.7500 1.6350 1.4300 JH0059pax 1 −0.5200 0.4200 −0.0500 −0.0650 0.6050 0.5050 JH0060pax 1 −0.7400 0.3250 0.0200 0.2900 0.6600 0.5100 JH0061pax 1 0.9900 2.8050 0.8700 1.4500 3.6400 0.8950 JH0063pax 1 −0.6100 0.5650 −0.2300 −1.0050 0.2750 1.5400 JH0065pax 1 −2.8600 −1.5150 −2.1500 −2.2300 −1.4500 −1.7100 JH0066pax 1 −1.3550 −0.3200 −1.1800 −1.7900 −1.3500 −0.5400 JH0068pax 1 0.0050 0.4550 0.2550 0.0200 1.3500 1.8000 JH0069pax 1 −0.8650 0.2450 −0.2650 −0.5000 −0.0500 −0.6400 JH0071pax 1 −2.5050 −2.2600 −1.8250 −0.3500 −1.3300 −1.5800 JH0072pax 1 0.1100 −0.5750 0.0350 −0.4650 1.3350 0.2300 JH0077pax 1 −0.1000 0.5000 0.4000 0.1150 0.8750 1.7850 JH0078pax 1 1.6350 1.6250 1.6300 0.6600 1.5100 1.7800 JH0080pax 1 −2.3200 −1.2350 −1.2600 −1.0250 −1.5600 0.0450 JH0082pax 1 −0.9000 −0.6650 −0.3200 −0.5450 −0.3550 0.7200 JH0083pax 1 −1.5800 −0.0750 −0.5300 −1.5900 0.2450 0.2050 JH0086pax 1 −0.2250 −0.1850 −0.4800 −1.3250 −0.0850 0.6800 JH0092pax 1 −0.5450 1.3750 0.0400 −0.1050 0.1300 1.1100 MH0001pax 1 1.4250 1.8900 1.5250 1.4350 3.1350 2.2700 MH0009pax 1 −0.2050 0.2150 −0.4850 −0.4450 −0.0400 −0.2050 MH0012pax 1 0.0650 1.3100 0.5700 1.0950 1.4000 1.1200 MH0014pax 1 0.6700 1.1300 0.6100 0.2850 2.6850 1.5750 MH0016pax 1 −1.0950 −0.6050 −0.6750 −1.2050 −0.2450 −0.4300 MH0017pax 1 −0.0100 0.8250 0.2000 −0.4150 1.2500 1.6250 MH0018pax 1 0.9650 0.6700 0.1850 0.2300 2.0650 0.5700 MH0021pax 1 0.9700 0.4800 −0.0650 0.2700 1.9100 1.8700 MH0022pax 1 0.2100 0.7250 0.1150 0.1250 0.8450 1.0950 MH0024pax 1 0.3450 0.6300 0.2050 −0.0550 0.3350 1.0900 MH0028pax 1 0.1350 0.5200 0.1350 −0.5950 0.1250 0.0850 MH0029pax 1 0.2300 0.4850 0.5700 −0.2050 1.3250 0.9050 MH0035pax 1 0.8900 2.2000 1.2200 0.9950 1.3300 1.9450 MH0037pax 1 0.0001 1.3400 0.2600 0.3800 1.5200 2.0000 MH0038pax 1 1.5050 1.4150 1.1650 1.2300 2.1700 1.9850 MH0039pax 1 −1.4900 −0.7350 −0.5400 −0.8300 −0.4350 0.4500 MH0042pax 1 −0.3500 −0.0800 0.0950 −0.2900 −0.1300 0.6500 MH0050pax 1 −1.2600 0.7250 −0.4300 −0.2350 1.1300 1.8350 MH0051pax 1 −1.0300 −0.9000 −0.5750 −1.4350 −1.9200 0.0300 MIP0004pax 1 −2.3200 −2.6150 −1.7200 −1.5500 −1.3550 −2.5350 MP0013Apax 1 0.3150 1.0550 −0.2400 0.0200 1.2450 −0.0700 MP0014Bpax 1 −0.2950 1.1200 −0.1400 0.2950 1.5600 0.3350 MP0018Apax 1 −0.7700 −0.2050 −0.6850 −1.4250 −0.1050 −1.1150 MP0019Bpax 1 −0.9100 −0.5150 −0.7550 −1.0250 −0.6750 0.7300 MP0024pax 1 −1.2900 −0.1150 −0.4700 0.2100 1.3100 0.7400 NK2001pax 1 −0.6250 0.0850 −0.4250 −1.2950 0.1750 1.6050 NK2002pax 1 −0.2400 −0.4300 −0.1450 −0.6550 0.2950 0.7000 NK2003pax 1 −0.4150 0.4150 0.0200 0.0950 1.4100 0.2550 NK2004pax 1 −0.9100 0.3750 −0.6100 −0.8750 0.3500 −0.2700 PB1829pax 1 0.5600 1.7600 0.3700 0.2100 1.8100 1.9150 PB1842pax 1 1.2550 1.6150 1.1550 0.5300 2.5900 1.3450 PB1872pax 1 0.0650 0.3550 0.2400 −0.8650 0.8650 0.0950 PB2857pax 1 −0.8600 0.6800 −0.2350 0.3500 0.0450 1.2500 RC2919pax 1 1.8500 1.8900 1.4100 2.7600 2.8200 3.8300 RC3062pax 1 −0.1750 0.1900 −0.3350 −0.0750 −0.2800 −0.0100 RC3277pax 1 −0.4200 −0.1950 −0.5050 −0.4350 0.3200 −0.0200 RC3297pax 1 0.0600 0.9800 0.1650 0.3850 2.5650 1.0450 RC3445pax 1 −1.0200 −0.4350 −0.6300 −0.9300 0.3100 0.1100 RC3467pax 1 1.9450 2.9300 1.4200 1.2250 2.9400 2.6000

Surprisingly, analysis of the data showed that RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 is present on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 15). The ranges of fold-change in the levels of RNA encoded by these genes normalized to levels of RNA encoded by IL2RB in blood of the training set subjects having colorectal cancer relative to the training set subjects not having any colorectal pathology are shown in Table 15.

TABLE 15 Sample training set ranges of fold-change in levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized RNA level in −0.32 0.41 0.78 −0.06 −0.13 0.64 subjects having colorectal cancer (ΔCt) Average normalized RNA level in 0.46 0.99 1.44 0.39 0.65 1.25 subjects not having any colorectal pathology (ΔCt) Average RNA level fold-change 1.71 1.50 1.58 1.37 1.72 1.53 p-value for average RNA level fold- 1.1E−08 1.0E−05 8.8E−06 2.3E−06 2.8E−12 6.3E−06 change Maximum observed RNA level 12.33 12.20 12.81 6.15 7.38 13.83 directional fold-change

As can be seen in Table 15, a test subject having a blood level of RNA encoded by ANXA3, normalized to a level of RNA encoded by IL2RB, which is 1.7 to 12.3 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 15, a test subject having a blood level of RNA encoded by CLEC4D, normalized to a level of RNA encoded by IL2RB, which is 1.5 to 12.2 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 15, a test subject having a blood level of RNA encoded by LMNB1, normalized to a level of RNA encoded by IL2RB, which is 1.6 to 12.8 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 15, a test subject having a blood level of RNA encoded by PRRG4, normalized to a level of RNA encoded by IL2RB, which is 1.4 to 6.2 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 15, a test subject having a blood level of RNA encoded by TNFAIP6, normalized to a level of RNA encoded by IL2RB, which is 1.7 to 7.4 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 15, a test subject having a blood level of RNA encoded by VNN1, normalized to a level of RNA encoded by IL2RB, which is 1.5 to 13.8 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Generation of a logistic regression model (optimized relative to the models set forth in Example 3 of the Examples section, above) for determining the probability that a test subject has colorectal cancer versus not having any colorectal pathology via measurement of levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB: Linear regression analysis of levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to IL2RB surprisingly showed that a logistic regression model could be generated, based on blood expression levels normalized to IL2RB for the combination of these 6 genes, for discriminating, with a ROC AUC of 0.80, between subjects having colorectal cancer and subjects not having any colorectal pathology (model #191 shown in Table 16).

The model of Table 16 corresponds to:

P={1+ê−[(0.126)+(−1.406)(L _(ANXA3))+(0.399)(L _(CLEC4D))+(1.874)(L _(LMNB1))+(−1.846)(L _(PRRG4))+(0.333)(L _(TNFAIP6))+(−0.277)(L _(vNN1))]}̂−1,

where P is the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, where L_(ANXA3) is a ratio of a level of RNA encoded by ANXA3 to a level of RNA encoded by IL2RB in blood of the test subject, L_(CLEC4D) is a ratio of a level of RNA encoded by CLEC4D to a level of RNA encoded by IL2RB in blood of the test subject, L_(LMNB1) is a ratio of a level of RNA encoded by LMNB1 to a level of RNA encoded by IL2RB in blood of the test subject, L_(PRRG4) is a ratio of a level of RNA encoded by PRRG4 to a level of RNA encoded by IL2RB in blood of the test subject, L_(TNFAIP6) is a ratio of a level of RNA encoded by TNFAIP6 to a level of RNA encoded by IL2RB in blood of the test subject, and L_(VNN1) is a ratio of a level of RNA encoded by VNN1 to a level of RNA encoded by IL2RB in blood of the test subject.

TABLE 16 Logistic regression model based on blood expression levels for the combination of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, normalized to IL2RB expression levels for determining the probability that a test subject has colorectal cancer as opposed to not having colorectal cancer. The ROC AUC value for the model is shown for the sample training set used to generate the models, as well as for an independent blind sample test set used to test the model. No. of Logistic genes ROC AUC Gene-specific regression coefficient Regression in Training Test Constant (K_(n)) Model # Model Set Set (K₀) ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 191 6 0.80 0.80 0.126 −1.406 0.399 1.874 −1.846 0.333 −0.277

Blind sample test set: Quantitative reverse transcriptase-PCR analysis of expression of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 in an independent test set of blood samples from 202 subjects having colorectal cancer and 208 subjects not having any colorectal pathology was performed as described above for the training set (these samples include a subset of the samples listed in Table 12 of Example 3, above, as well as additional samples). The normalized RNA levels measured are shown in Table 17.

TABLE 17 Sample test set levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 in blood of subjects having colorectal cancer (Group 1) and subjects not having any colorectal pathology (Group 0), normalized to levels of RNA encoded by IL2RB. Levels shown correspond to ΔCt. Gene Sample ID Group ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 PB1952pax 0 2.240 2.125 0.965 2.285 3.220 2.520 RC3142pax 0 2.795 2.380 1.225 2.040 2.675 2.500 CD1728pax 0 2.410 2.330 1.835 2.465 2.345 3.715 PB2015pax 0 2.250 1.835 2.075 3.010 4.220 2.390 PB1786pax 0 1.210 2.530 1.085 2.310 1.555 3.185 CD0762pax 0 1.215 1.260 1.140 2.360 1.925 1.730 CD0800pax 0 2.410 2.310 1.550 2.210 3.480 2.795 PB3267pax 0 1.885 2.565 1.285 2.180 2.325 2.575 PB2267pax 0 2.160 2.890 1.505 2.215 3.085 2.895 CD0411pax 0 2.510 2.950 1.900 2.365 3.890 3.660 CD0211pax 0 1.115 2.235 1.350 2.650 2.470 2.310 PB1918pax 0 2.450 2.080 1.145 1.590 3.675 2.435 PB0701pax 0 1.220 2.090 1.760 2.655 2.190 3.785 PB3445pax 0 1.400 1.870 1.015 1.955 2.280 2.205 PB1763pax 0 2.035 2.435 1.720 2.490 2.975 1.785 PB3213pax 0 2.245 2.340 1.390 1.795 2.255 2.100 CD1424pax 0 1.460 1.300 1.220 1.975 2.535 2.510 PB2978pax 0 2.945 3.175 1.990 2.175 3.680 2.840 PB3270pax 0 1.895 3.055 0.885 1.415 1.280 2.545 RC2030pax 0 1.580 2.060 1.205 1.595 1.665 4.080 CD0448pax 0 2.195 2.955 1.800 2.400 4.090 3.800 RC2869pax 0 1.620 1.415 0.880 1.475 2.500 2.520 PB4296pax 0 1.940 2.600 1.445 1.765 2.290 3.890 CD0398pax 0 2.425 2.560 1.970 2.265 4.015 3.515 CD1077pax 0 0.740 0.845 0.575 1.560 1.410 1.560 PB3805pax 0 2.040 1.655 1.515 1.605 1.020 1.610 PB1898pax 0 2.075 2.445 1.180 1.800 3.165 1.410 PB2062pax 0 2.090 2.110 1.455 1.850 3.090 2.220 CD0937pax 0 1.120 0.705 0.655 1.365 2.310 1.860 RC2612pax 0 2.725 2.685 1.810 1.830 3.395 2.535 CD1784pax 0 1.615 1.410 1.325 1.735 2.325 2.325 PB2984pax 0 1.205 2.325 0.990 1.895 2.270 2.315 RC2976pax 0 −0.045 1.445 −0.305 0.685 −0.305 3.570 PB1785pax 0 1.470 1.950 1.245 1.880 1.835 1.450 CD0691pax 0 1.785 2.850 1.445 2.060 2.535 1.900 PB2384pax 0 1.700 2.440 0.915 1.380 2.500 2.405 CD1550pax 0 2.420 3.640 2.150 2.235 3.065 3.690 CD1540pax 0 1.005 0.905 0.785 1.465 1.745 0.990 RC2565pax 0 −0.125 0.690 −0.330 0.735 0.200 1.790 CD0499pax 0 1.390 2.750 0.805 1.720 2.820 1.290 RC2174pax 0 0.440 1.020 0.790 1.700 1.705 2.265 PB3304pax 0 0.550 1.270 0.520 1.760 2.765 0.835 PB1879pax 0 1.345 1.065 1.295 1.620 2.070 1.830 PB3808pax 0 1.450 1.405 1.225 1.580 2.810 2.435 PB4357pax 0 1.065 0.195 0.295 0.690 1.245 0.360 PB2636pax 0 1.795 2.615 1.360 1.775 3.600 2.925 PB3440pax 0 1.320 1.720 1.280 1.515 0.640 1.495 PB2272pax 0 2.225 2.130 1.335 1.475 3.785 1.805 PB1848pax 0 1.410 1.150 0.765 0.875 2.300 2.775 RC3420pax 0 1.265 1.490 1.390 2.060 2.875 0.995 PB2005pax 0 1.800 1.830 1.045 1.285 3.465 2.250 CD0354pax 0 0.680 1.160 0.585 1.395 2.015 1.265 CD1945pax 0 1.005 1.500 0.260 0.815 2.430 2.055 PB4156pax 0 2.005 2.405 1.435 1.370 1.995 1.990 RC2934pax 0 1.055 1.185 0.605 1.025 2.760 2.560 PB2214pax 0 1.350 1.790 0.535 0.980 2.390 1.315 PB3370pax 0 0.965 2.430 1.125 1.795 1.985 2.235 PB1300-2pax 0 0.885 1.535 0.425 0.960 1.765 1.860 PB2951pax 0 −0.180 −1.980 −1.215 −0.650 −0.520 −0.915 PB3356pax 0 −0.430 1.050 −0.145 1.105 0.680 1.550 CD0148pax 0 0.740 1.890 0.515 1.255 1.835 1.665 PB3451pax 0 1.240 1.300 0.720 1.025 2.210 1.555 CD1409pax 0 0.510 0.115 0.140 0.495 0.660 1.250 PB3118pax 0 1.480 1.615 1.415 1.375 1.195 1.855 PB3931pax 0 1.460 1.515 0.925 1.250 2.790 1.210 CD1163pax 0 1.105 2.110 1.475 2.175 3.175 1.875 RC2112pax 0 1.255 2.285 1.555 1.830 1.825 2.530 PB4274pax 0 0.670 0.385 0.075 0.245 0.535 1.735 CD1028pax 0 1.250 2.115 0.985 1.370 2.240 1.950 PB4345pax 0 0.680 1.445 0.895 1.320 1.125 2.145 CD0698pax 0 0.925 1.555 0.915 1.295 1.265 1.515 PB4066pax 0 0.855 0.175 0.580 0.940 1.450 0.185 PB4062pax 0 0.720 1.380 0.455 1.305 2.385 0.300 PB3481pax 0 −0.110 0.835 0.185 1.025 0.445 1.345 CD0252pax 0 1.100 0.340 0.380 0.615 2.185 0.580 CD0428pax 0 0.480 1.090 0.225 0.815 1.420 1.465 CD0571pax 0 1.060 1.425 1.430 1.960 2.575 0.890 CD0786pax 0 0.850 1.335 0.795 1.290 2.045 1.325 PB3863pax 0 1.745 1.785 1.435 1.255 2.620 2.605 PB2927pax 0 1.955 0.820 0.520 −0.140 1.515 1.890 PB3568pax 0 1.505 1.625 1.250 1.295 2.155 1.370 RC2839pax 0 0.690 1.275 0.595 0.935 1.195 1.800 CD1700pax 0 1.095 1.520 1.160 1.250 1.480 2.020 CD1313pax 0 1.600 1.400 0.710 0.820 2.670 0.510 PB1700pax 0 0.690 1.020 0.740 1.155 1.610 1.265 CD0727pax 0 1.515 2.780 1.015 1.245 2.130 1.450 PB4161pax 0 0.940 0.945 0.755 0.890 1.340 1.330 CD1583pax 0 0.690 0.855 0.530 0.780 1.240 1.445 PB3594pax 0 0.885 1.175 0.500 0.935 2.395 1.040 RC3170pax 0 0.860 1.635 0.190 0.210 0.400 2.110 CD0553pax 0 2.075 3.365 1.750 1.505 2.725 3.125 CD0220pax 0 1.080 2.120 1.110 1.210 1.380 2.345 CD0238pax 0 0.355 1.010 0.440 1.065 1.720 1.180 CD0409pax 0 −0.235 0.710 −0.100 0.650 0.505 1.320 PB3163pax 0 0.530 1.630 0.885 1.515 2.675 2.245 PB2491pax 0 0.835 −0.035 0.295 0.605 2.505 0.150 PB4377pax 0 0.110 0.315 0.030 0.565 1.245 1.270 PB4307pax 0 1.845 3.790 1.730 1.775 3.650 3.665 RC2236pax 0 0.970 1.080 1.035 0.985 1.450 2.095 RC2716pax 0 0.490 0.730 0.845 1.360 2.490 1.365 PB2024pax 0 0.815 1.375 0.785 1.075 2.445 1.850 CD0484pax 0 0.140 1.135 0.255 1.080 1.585 0.255 RC2897pax 0 0.385 1.035 0.130 0.530 1.350 1.335 CD0872pax 0 0.580 −0.005 0.490 0.585 1.435 1.005 PB1626pax 0 0.525 0.835 0.435 0.550 1.075 1.865 CD1974pax 0 0.965 1.445 0.350 0.555 2.000 0.985 CD1295pax 0 0.560 0.450 0.425 0.560 1.575 1.570 RC2699pax 0 0.825 1.015 0.340 0.395 1.385 1.285 RC2986pax 0 1.095 1.315 0.540 0.625 2.675 1.710 PB1899pax 0 −0.230 0.420 −0.365 0.095 0.270 1.625 PB3955pax 0 1.630 1.745 1.220 1.070 3.000 1.545 PB1230pax 0 0.685 1.585 0.855 0.955 0.950 1.870 CD1404pax 0 −0.045 1.190 0.225 0.740 1.330 2.630 CD0367pax 0 1.050 0.940 0.745 0.705 2.105 1.360 PB3226pax 0 0.720 1.225 0.760 1.010 2.320 1.735 PB3193pax 0 0.475 0.650 0.650 0.905 1.600 1.205 PB3224pax 0 0.400 −0.115 0.080 0.125 0.415 0.390 PB1871pax 0 0.715 0.640 0.565 0.545 1.590 1.710 CD1392pax 0 1.055 1.540 0.860 1.030 2.995 1.720 CD0833pax 0 −0.050 −0.365 −0.090 0.365 0.630 −0.285 CD0386pax 0 1.070 2.390 1.000 1.280 3.245 2.350 CD1158pax 0 0.335 0.270 0.110 0.065 0.185 1.405 PB1324pax 0 −0.110 0.585 0.465 1.050 1.765 1.840 CD1455pax 0 −0.610 0.530 0.345 1.150 0.755 1.570 RC2338pax 0 1.395 2.355 1.590 1.460 2.515 2.445 CD1971pax 0 0.645 1.425 0.060 0.110 1.400 2.170 CD1048pax 0 0.860 2.110 1.115 1.525 2.600 1.210 CD0244pax 0 0.285 0.305 0.260 0.670 1.395 −0.095 RC3191pax 0 1.560 2.415 1.510 1.210 2.285 2.395 PB3582pax 0 1.090 1.830 1.230 1.320 2.870 1.955 CD0237pax 0 0.595 1.085 0.245 0.400 1.400 0.985 CD1981pax 0 1.955 3.135 1.875 1.495 3.520 3.250 CD0603pax 0 1.015 1.015 0.640 0.400 1.755 1.770 CD1134pax 0 0.795 1.655 0.815 0.790 1.850 2.475 PB2130pax 0 0.665 0.890 0.335 0.260 0.895 1.155 PB1275pax 0 −0.885 0.195 −0.445 0.145 −0.230 2.010 PB2564pax 0 0.385 1.960 0.460 0.810 1.055 1.265 CD0580pax 0 1.150 1.580 0.470 0.400 2.330 1.165 PB0768pax 0 −0.670 0.740 0.080 0.825 0.425 1.335 CD0518pax 0 1.575 3.770 1.750 1.775 3.120 2.440 RC3315pax 0 0.640 1.565 0.650 1.035 2.680 0.940 CD1270pax 0 0.895 1.020 0.770 0.515 1.695 1.680 CD1068pax 0 0.380 0.200 0.700 0.985 2.475 0.400 CD0995pax 0 0.805 1.465 0.560 0.615 2.395 1.435 CD1438pax 0 −0.125 0.620 −0.030 0.440 0.905 0.045 CD1169pax 0 0.270 0.295 0.470 0.500 1.845 1.430 RC3379pax 0 0.850 1.185 0.460 0.410 1.945 0.400 CD0520pax 0 −0.125 1.025 0.990 1.325 1.130 1.370 PB1718pax 0 0.145 1.185 0.395 0.445 0.695 1.505 PB2757pax 0 0.555 1.690 0.995 0.915 1.750 2.335 CD0743pax 0 0.290 −0.400 0.095 0.070 1.515 −0.120 CD0667pax 0 −0.385 −0.305 −0.345 −0.065 0.205 −0.230 RC3214pax 0 0.940 1.860 1.200 1.140 2.730 1.620 PB0689pax 0 0.235 1.420 0.295 0.270 0.905 1.990 CD0911pax 0 −0.550 −0.580 −0.800 −0.405 0.290 −0.560 PB2516pax 0 0.310 1.075 0.700 0.490 0.890 2.285 PB2584pax 0 0.945 1.230 0.935 0.475 1.270 1.340 CD1487pax 0 0.310 2.120 1.190 1.645 2.160 0.815 CD0282pax 0 0.165 0.685 0.270 0.545 1.100 −0.700 PB4325pax 0 0.065 −0.180 −0.020 −0.025 0.475 −0.360 RC2652pax 0 −1.425 0.025 −0.620 0.450 0.760 0.560 PB2464pax 0 0.620 1.330 0.510 0.045 1.230 2.810 PB3227pax 0 0.235 0.850 0.820 0.865 2.215 1.845 CD1559pax 0 0.170 1.000 0.335 0.505 2.070 1.300 PB4003pax 0 0.070 0.655 0.170 0.215 0.880 0.690 CD0108pax 0 0.260 0.055 0.560 0.310 0.740 0.640 PB1758pax 0 −0.600 0.475 0.030 0.535 0.500 0.145 CD0277pax 0 0.605 1.980 0.800 0.940 2.250 0.720 PB2184pax 0 −1.005 −0.650 −0.705 −0.445 −0.075 1.230 CD1683pax 0 0.485 1.620 0.725 0.575 1.595 1.805 RC2615pax 0 −0.655 0.070 0.210 0.340 0.190 1.205 CD1224pax 0 −0.295 0.630 −0.325 −0.110 0.995 0.485 CD1458pax 0 0.035 −0.055 0.560 0.485 1.635 0.585 CD0204pax 0 0.380 0.885 0.250 −0.050 1.200 0.990 CD1706pax 0 0.540 1.815 1.025 1.020 2.510 1.195 CD1542pax 0 0.375 0.870 0.900 0.655 1.755 1.305 PB2909pax 0 −0.345 −1.240 −0.675 −0.915 −0.075 −0.645 PB4073pax 0 −0.250 0.195 −0.095 −0.205 0.410 0.600 CD0604pax 0 0.415 1.130 0.320 0.235 2.125 0.230 PB3605pax 0 −1.120 −0.290 −0.695 −0.340 0.305 0.660 CD1965pax 0 0.030 1.310 0.400 0.140 1.155 2.275 CD0432pax 0 0.185 0.565 0.015 −0.140 1.870 0.495 PB1336pax 0 0.695 0.780 0.320 −0.470 1.310 1.805 PB2974pax 0 −0.635 0.320 −0.300 −0.305 0.605 1.740 PB0662pax 0 0.120 0.575 0.945 0.850 1.605 0.045 CD1741pax 0 −0.310 −0.335 0.015 −0.160 1.205 0.850 PB2875pax 0 −0.230 1.205 0.140 0.165 1.200 1.025 CD0419pax 0 0.440 1.220 0.810 0.655 2.375 −0.030 CD1649pax 0 0.925 1.565 1.000 0.130 1.550 1.630 CD1329pax 0 0.130 −0.170 0.155 −0.460 1.075 0.705 CD0466pax 0 0.730 1.870 0.930 0.160 1.280 1.890 CD0857pax 0 −1.460 −0.755 −0.560 −0.360 −0.670 0.255 CD0242pax 0 0.965 1.360 0.580 −0.450 0.980 1.235 PB3513pax 0 −0.355 −0.705 −0.970 −1.200 0.410 −1.270 CD0583pax 0 −0.605 −1.045 −0.595 −0.740 0.765 −0.705 PB3049pax 0 −1.030 0.045 −0.235 −0.170 0.105 0.595 PB1446pax 0 −1.380 −0.485 −0.715 −0.495 0.300 0.700 CD1441pax 0 −0.565 0.485 0.230 0.175 0.995 0.055 PB2634pax 0 0.165 1.335 1.270 1.000 2.740 1.020 CD0547pax 0 −1.740 −0.260 −0.685 −0.185 −0.095 −0.420 PB2041pax 0 −0.655 0.440 −0.205 −0.170 1.540 0.185 PB1514pax 0 −0.940 0.075 −0.280 −0.265 0.850 0.175 PB3032pax 0 −0.145 0.435 0.750 0.110 1.510 1.425 CD0676pax 0 −0.730 −0.640 −0.610 −1.085 0.300 0.100 PB3806pax 0 −1.410 0.325 −0.305 −0.080 −0.010 −0.070 CD0472pax 0 −1.800 −0.180 −0.830 −0.465 0.255 −0.070 PB1222pax 0 −0.165 0.415 0.325 −0.795 −0.035 0.860 CD1032pax 0 −2.740 −2.045 −0.550 −0.490 −0.875 0.410 JH0111pax 1 1.040 1.910 0.835 2.170 2.645 1.650 MH0122Bpax 1 0.235 1.190 0.340 1.380 0.430 3.590 IS3001pax 1 1.925 2.145 1.030 1.300 1.885 2.880 BE3003pax 1 0.985 1.160 1.050 1.985 2.185 1.120 MH0083pax 1 1.570 1.635 0.805 1.195 2.150 1.765 BE1004pax 1 0.085 1.050 0.730 1.825 2.040 1.790 MH0112Bpax 1 0.960 1.720 0.810 1.325 1.975 2.055 BE1007pax 1 1.050 0.945 0.815 1.055 1.810 2.100 MH0031-2pax 1 −0.325 −0.130 −0.430 0.615 1.330 1.170 MH0112Apax 1 0.925 1.760 1.025 1.500 2.025 2.220 MR4001Apax 1 0.610 1.130 0.470 1.210 1.650 0.615 NK2011pax 1 1.355 2.025 1.060 1.110 2.520 3.570 OL0092pax 1 0.790 1.555 0.670 1.160 1.585 1.650 MIP2007pax 1 1.075 1.725 0.855 1.265 2.410 1.980 JH0153pax 1 1.085 1.470 0.610 0.580 0.495 2.085 KW0005pax 1 0.695 1.540 1.240 1.940 2.705 1.850 JH0054pax 1 0.555 1.775 0.870 1.580 1.990 1.710 AN4017pax 1 1.190 1.630 0.590 0.510 0.620 1.665 MP0031Apax 1 1.090 1.315 0.705 0.800 1.720 1.570 MP0021Bpax 1 0.410 0.995 0.710 1.220 1.765 1.555 MIP1018Bpax 1 0.600 1.535 0.490 1.020 1.720 1.115 CC0005pax 1 0.655 0.940 0.345 0.725 1.460 0.345 NK1009pax 1 1.915 1.845 1.030 0.650 2.595 1.635 JM0010pax 1 0.130 0.610 0.670 1.075 1.260 1.775 JH0150pax 1 0.895 1.930 0.490 0.685 0.900 0.730 IS1004pax 1 1.495 2.710 1.750 1.520 2.570 3.730 MIP1021Bpax 1 0.600 2.605 0.860 1.455 2.305 2.180 NK5006pax 1 0.895 1.205 0.645 0.620 2.095 2.495 MP0032Bpax 1 0.630 1.060 0.315 0.640 1.770 0.865 BE3012Apax 1 −0.830 −0.545 −1.045 −0.330 −0.330 0.700 JH0146pax 1 −0.130 0.615 0.175 0.805 1.540 1.665 NK2007pax 1 0.110 0.520 −0.030 0.560 0.980 −0.125 JH0112pax 1 0.500 0.910 0.265 0.530 1.635 1.090 OL0066pax 1 0.140 1.050 0.380 0.785 1.140 1.410 DC0012pax 1 −1.370 −0.520 −0.775 0.275 −1.140 −0.350 JH0129pax 1 0.580 1.530 0.935 1.265 2.850 2.270 JH0163pax 1 0.295 1.490 0.955 1.580 2.625 1.310 FS0005pax 1 0.040 0.315 0.500 0.890 1.355 0.850 DES1006Apax 1 0.955 1.140 0.890 0.635 1.570 1.940 MH0030pax 1 −0.150 0.865 0.180 0.720 0.345 0.260 FS0006pax 1 0.100 0.195 0.585 0.825 1.165 1.025 OL0096pax 1 0.305 1.230 0.890 0.830 0.405 2.550 MIP2003pax 1 −0.045 0.665 0.295 0.835 1.865 1.060 MH0113Apax 1 0.495 0.085 0.800 0.575 1.015 1.565 JH0067pax 1 0.230 0.940 0.100 0.355 1.180 0.980 MH0053pax 1 2.195 2.465 1.420 0.670 3.315 2.550 MW0001Apax 1 0.345 1.160 0.540 0.680 1.290 1.545 AN4013pax 1 1.135 2.150 1.055 0.770 1.810 2.225 WJ0005CSpax 1 −0.895 −0.630 −1.440 −0.840 0.055 0.250 JH0096pax 1 −1.745 −0.480 −1.130 −0.400 −2.050 1.375 DC5008Bpax 1 0.045 0.855 0.140 0.300 1.415 2.280 MIP2002pax 1 1.120 1.680 1.060 0.755 2.000 1.890 AN0011pax 1 1.110 1.075 0.125 −0.780 0.320 2.935 DES1009Apax 1 0.305 0.660 0.325 0.440 0.955 0.370 DC0011pax 1 0.150 0.700 0.615 0.730 1.535 1.880 FC0013pax 1 −0.105 −0.095 0.920 0.965 1.255 2.145 OL0075pax 1 −0.590 0.190 −0.010 0.590 1.140 0.970 NK2014pax 1 0.485 1.240 0.650 0.745 1.705 1.100 KW0008pax 1 0.090 0.985 0.305 0.250 0.220 1.730 OL0080pax 1 −0.445 −0.025 −0.150 0.110 0.030 0.540 AN4019pax 1 1.520 2.265 1.045 0.765 3.090 1.225 JH0116pax 1 0.035 1.465 0.520 0.830 1.040 1.120 JH0132pax 1 −0.460 0.010 −0.310 0.095 0.365 −0.005 JH0170pax 1 2.050 2.960 1.645 0.855 3.655 3.370 NK1001pax 1 0.415 0.990 −0.050 −0.025 1.805 0.975 OL0065pax 1 0.280 0.730 0.445 0.530 1.630 0.690 BE3011Apax 1 0.640 1.825 0.600 0.680 2.150 1.105 KW0004pax 1 0.895 2.485 1.415 1.290 1.975 1.935 JH0022pax 1 −0.265 0.255 0.040 0.145 0.375 0.945 JH0100pax 1 0.550 1.420 1.020 0.955 1.955 1.405 CD1690pax 1 0.120 0.145 0.110 0.165 1.040 −0.315 MH0063pax 1 0.265 −0.295 −0.305 −0.215 2.185 −0.590 MIP1017pax 1 −0.260 0.825 −0.250 0.000 0.670 0.800 JH0109pax 1 1.190 2.160 1.000 0.405 2.055 2.640 CC0001pax 1 0.170 0.765 0.295 0.315 1.785 1.305 PB3545pax 1 −0.520 1.150 −0.380 0.170 0.795 0.475 IS4001pax 1 −0.855 −0.065 −0.915 −0.770 −0.370 1.630 DC0005pax 1 1.085 1.960 1.220 0.715 1.895 1.965 MH0070pax 1 0.380 0.945 0.685 0.515 1.575 1.395 JH0114pax 1 −1.875 −1.485 −1.400 −0.540 −1.710 −1.970 CD1351pax 1 0.510 0.515 0.015 −0.295 1.830 0.785 OL0093pax 1 −2.055 −0.120 −1.075 0.025 −0.430 0.560 JH0058pax 1 −0.610 0.305 0.165 0.240 −0.060 1.195 DC5008Apax 1 −0.395 0.160 −0.190 −0.155 1.135 1.540 OL0085pax 1 −0.985 −0.050 −0.750 −0.290 0.505 0.520 FS1022pax 1 −0.530 0.295 0.400 0.675 0.655 0.040 OL0063pax 1 −0.915 −0.430 −0.335 −0.025 0.055 −0.085 MH0108Apax 1 0.215 0.810 0.225 −0.005 0.885 0.570 MIP2006pax 1 −0.590 0.470 −0.025 0.265 0.505 0.080 NK2016pax 1 −0.220 0.425 0.075 0.215 1.975 0.835 OL0057pax 1 −0.975 −0.970 −1.340 −1.210 −0.630 −0.575 JH0137pax 1 0.265 1.395 0.095 −0.125 1.190 1.175 JH0118pax 1 0.030 −0.565 0.010 −0.405 0.610 0.125 MH0097pax 1 −0.785 −0.180 −0.195 −0.015 0.345 0.430 JH0147pax 1 0.770 2.080 0.915 0.855 3.475 1.255 BE4002pax 1 0.160 0.420 0.015 −0.445 0.760 1.265 MH0036pax 1 −0.090 0.620 0.370 0.240 1.430 1.440 JH0142pax 1 −0.585 0.220 −0.185 0.055 0.285 −0.605 MIP2010Apax 1 0.285 0.555 −0.075 −0.280 1.550 −0.070 JH0169pax 1 −0.305 0.255 −0.120 −0.320 0.455 1.110 FS1010pax 1 0.435 1.705 1.210 0.800 1.520 2.145 JGA0036pax 1 −0.515 0.390 −0.595 −0.995 −0.725 2.090 MH0079pax 1 0.395 0.625 0.275 −0.375 0.500 1.020 OL0064pax 1 0.030 0.500 0.305 0.120 1.345 0.580 JH0135pax 1 −1.480 −1.890 −1.505 −1.320 −1.655 −1.480 OL0017pax 1 −0.790 −0.650 −0.375 −0.315 0.900 0.765 CC2001pax 1 −0.285 1.450 0.335 0.480 1.315 1.210 DC6002Apax 1 −0.570 0.975 0.200 0.395 0.930 1.000 JH0149pax 1 0.485 1.165 0.240 −0.065 2.395 0.980 DC2009pax 1 −0.715 0.050 0.195 0.155 −0.350 0.365 MP0033Bpax 1 0.145 1.045 0.320 0.075 1.285 0.715 MP0030Bpax 1 −0.875 0.445 0.270 0.690 2.285 1.790 JH0133pax 1 −0.335 0.500 0.045 −0.220 0.210 1.150 OL0059pax 1 −1.335 −0.180 −0.735 −0.290 −0.065 −0.145 AN4026Bpax 1 −0.175 0.485 0.215 −0.160 0.510 1.130 AN4022Apax 1 −0.540 0.830 −0.290 −0.355 0.020 0.710 OL0077pax 1 −1.055 −0.525 −0.085 0.035 0.200 0.165 OL0094pax 1 −0.305 0.535 0.190 0.015 0.710 0.460 KW0002pax 1 −0.625 0.165 −0.505 −0.695 0.470 1.215 MH0066pax 1 −1.180 −0.855 −0.710 −0.595 −0.320 −0.480 DC5006Apax 1 −0.210 0.160 0.105 −0.385 −0.220 0.280 NK4001pax 1 −0.975 1.135 −0.090 0.260 0.500 0.810 JGA0029pax 1 −0.870 0.590 −0.575 −0.195 1.295 0.185 MW0008Apax 1 −1.080 −0.505 −0.480 −0.440 −0.300 −0.285 JH0131pax 1 −0.640 −0.890 −0.935 −1.555 −1.150 0.180 JH0106pax 1 −0.720 −0.200 −0.105 −0.290 0.845 1.115 OL0056pax 1 −0.495 −1.310 −0.470 −0.925 1.175 0.450 MH0076pax 1 0.515 1.955 0.540 −0.075 2.340 2.570 NK2005pax 1 −1.575 −1.090 −0.925 −1.055 −2.160 −0.020 MP0029Apax 1 −1.700 −0.870 −1.100 −0.670 0.275 0.060 MH0080pax 1 −0.310 0.215 0.340 0.120 1.530 0.510 FS1014pax 1 −0.580 0.050 −0.030 0.045 1.850 −0.105 JH0110pax 1 −0.565 0.185 −0.375 −0.830 −0.420 0.735 JH0145pax 1 −2.030 −0.365 −0.940 −0.500 −1.170 0.445 MH0125Apax 1 −0.550 1.265 0.135 −0.170 0.465 2.310 OL0058pax 1 −0.935 −1.050 −0.840 −0.870 0.115 −1.495 DC0008pax 1 0.545 0.990 0.665 −0.070 1.875 0.815 MH0073pax 1 −1.290 −0.595 −1.165 −1.040 0.040 −0.285 MIP0002pax 1 −2.285 −0.925 −1.240 −0.595 −0.575 0.055 JH0138pax 1 −0.680 0.150 −0.065 −0.315 0.120 0.340 OL0074pax 1 −1.255 −0.530 −0.680 −0.410 1.280 0.145 OL0079pax 1 −0.920 −0.125 −0.510 −0.755 −0.360 0.460 MR1001pax 1 −0.120 0.795 0.015 −0.490 0.650 0.495 DES5001Bpax 1 −1.335 0.395 −1.095 −0.735 0.770 0.315 MH0093pax 1 −2.215 −1.375 −1.240 −0.880 −0.800 0.255 MP0027Apax 1 −0.415 0.765 −0.140 −0.350 0.940 0.200 IS1005Apax 1 −1.180 −1.030 −0.340 −0.445 0.325 −0.025 KW0003pax 1 −0.295 0.830 0.335 −0.580 −0.325 2.740 CD1260pax 1 −0.730 −1.005 −0.325 −0.795 0.725 0.510 JH0130pax 1 −1.110 −0.400 −0.940 −1.210 −0.505 0.220 MH0096pax 1 −1.225 0.790 −0.670 −0.420 0.865 0.665 OL0052pax 1 −1.075 −1.005 −0.060 −0.315 0.040 −0.265 MIP0005pax 1 −2.020 −1.140 −1.305 −0.835 −0.420 −1.190 OL0014pax 1 −2.000 −2.250 −1.480 −1.640 −1.645 −0.705 WJ0003RTpax 1 −1.935 −1.860 −1.760 −1.735 −1.070 −1.055 MIP2013Bpax 1 0.025 1.825 0.110 −0.890 −0.500 1.975 JH0164pax 1 −0.115 0.335 0.015 −0.615 1.275 0.005 JH0123pax 1 −2.050 −1.365 −1.125 −0.920 −1.165 −1.315 OL0089pax 1 −1.415 0.130 −0.455 −0.365 −0.305 −0.520 DES1013Bpax 1 −1.130 0.105 −0.450 −0.595 0.160 0.065 AN4011pax 1 −0.155 0.805 0.770 0.280 2.110 0.880 JH0093pax 1 0.095 1.090 0.085 −0.695 1.290 0.885 OL0043pax 1 −0.705 −0.475 −0.555 −1.105 0.230 −0.335 JH0097pax 1 −0.280 −0.285 0.270 −0.445 0.780 −0.415 DC3003pax 1 −0.265 0.975 0.030 −0.625 1.600 1.845 OL0068pax 1 −1.790 −0.720 −1.340 −1.230 −0.665 −0.895 KW0006pax 1 −1.320 0.575 0.155 0.080 0.700 1.540 NK5008pax 1 −1.150 −1.435 −1.000 −1.300 0.610 −1.040 DC6001Apax 1 −0.965 0.725 −0.225 −0.670 0.135 1.500 OL0034pax 1 −1.155 −0.515 −0.985 −1.375 0.485 0.545 MH0062pax 1 −1.040 −0.245 −0.205 −0.600 0.450 0.300 MIP1019Apax 1 −1.415 −0.495 −1.060 −1.125 0.800 −0.060 MR1002pax 1 −0.890 0.295 0.315 −0.070 0.645 0.355 MH0090pax 1 −0.995 0.240 −0.365 −0.705 0.000 −0.495 NK2010pax 1 −1.505 −1.070 −0.985 −1.320 −0.870 −1.045 NK2009pax 1 0.060 0.745 0.470 −0.370 1.920 0.300 NK2018pax 1 −2.160 −1.415 −1.155 −1.090 −0.640 −1.100 JH0144pax 1 0.475 2.560 1.160 0.215 2.295 1.575 OL0078pax 1 −2.540 −2.250 −1.570 −1.555 −1.350 −1.325 MIP1009pax 1 −2.950 −1.590 −2.030 −1.500 −0.685 −1.165 OL0025pax 1 −2.010 −0.060 −0.940 −0.855 −0.380 −0.445 MH0078pax 1 −0.910 0.290 −0.405 −1.410 −0.335 1.345 KW0007pax 1 −0.655 0.930 0.090 −0.640 0.830 0.495 AN0013pax 1 0.060 1.905 0.875 −0.085 2.740 2.020 JH0076pax 1 −0.535 −0.795 −0.360 −1.735 −0.300 −0.065 OL0090pax 1 −1.105 0.150 0.090 −0.745 0.075 0.990 JH0120pax 1 −0.040 0.595 0.215 −0.935 1.860 0.390 JH0126pax 1 −1.570 −0.110 −0.455 −1.020 −0.435 0.415 JH0113pax 1 −0.055 0.805 0.605 −0.715 0.835 0.570 JH0085pax 1 −0.960 −0.445 −0.075 −1.095 0.185 0.295 MH0081pax 1 0.390 1.375 0.640 −0.845 2.085 1.300 AN0001pax 1 −1.830 −1.010 −0.840 −1.320 0.110 −0.175 MH0095pax 1 −2.145 −1.475 −1.350 −1.795 −0.915 −0.830 DS0007pax 1 −3.365 −2.210 −1.965 −1.820 −3.555 −2.965 JH0136pax 1 −2.355 −1.670 −0.970 −1.215 −0.845 −1.710 OL0072pax 1 −1.135 −0.315 −0.375 −1.170 0.415 −0.875 BE1006pax 1 −2.635 −1.570 −1.580 −1.735 −0.580 −0.740 JH0048pax 1 −2.285 −0.250 −1.315 −1.350 −1.075 −2.025 OL0073pax 1 −2.980 −2.425 −1.650 −1.685 −0.100 −0.650 FS0002pax 1 −2.275 −1.035 −0.730 −1.030 −0.780 −1.700 OL0041pax 1 −1.890 −1.030 −1.595 −2.325 −0.970 −1.465 AN0007pax 1 −3.105 −1.775 −2.300 −3.180 −2.690 −1.255

The test set results confirmed the surprising finding based on the training set that ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 each express RNA on average at a significantly higher level (p-value less than 0.05) in blood of subjects having colorectal cancer relative to subjects having no colorectal pathology (Table 18). The ranges of fold-change in the levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of the test set subjects having colorectal cancer relative to the test set subjects not having any colorectal pathology are also shown in Table 18.

TABLE 18 Sample test set ranges of fold-changes in levels of RNA encoded by ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1 normalized to levels of RNA encoded by IL2RB in blood of subjects having colorectal cancer relative to subjects not having any colorectal pathology. Gene ANXA3 CLEC4D LMNB1 PRRG4 TNFAIP6 VNN1 Average normalized RNA level in subjects −0.37 0.39 −0.04 −0.07 0.76 0.74 having colorectal cancer (ΔCt) Average normalized RNA level in subjects 0.72 1.21 0.65 0.90 1.73 1.51 not having any colorectal pathology (ΔCt) Average RNA level fold-change 2.12 1.77 1.61 1.97 1.95 1.70 p-value for average RNA level fold-change 2.8E−24 3.0E−14 3.3E−19 1.9E−26 5.0E−17 2.4E−12 Maximum observed RNA level directional 16.95 12.44 7.71 16.96 38.96 22.19 fold-change

As can be seen in Table 18, a test subject having a blood level of RNA encoded by ANXA3, normalized to a level of RNA encoded by IL2RB, which is 2.1 to 17.0 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 18, a test subject having a blood level of RNA encoded by CLEC4D, normalized to a level of RNA encoded by IL2RB, which is 1.8 to 12.4 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 18, a test subject having a blood level of RNA encoded by LMNB1, normalized to a level of RNA encoded by IL2RB, which is 1.6 to 7.7 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 18, a test subject having a blood level of RNA encoded by PRRG4, normalized to a level of RNA encoded by IL2RB, which is 2.0 to 17.0 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 18, a test subject having a blood level of RNA encoded by TNFAIP6, normalized to a level of RNA encoded by IL2RB, which is 2.0 to 39.0 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

As can be seen in Table 18, a test subject having a blood level of RNA encoded by VNN1, normalized to a level of RNA encoded by IL2RB, which is 1.7 to 22.2 fold higher than the average level of RNA encoded by this gene in blood of subjects not having any colorectal pathology is more likely to have colorectal cancer than to not have any colorectal pathology.

Furthermore, the test set results confirmed the surprising finding based on the training set that logistic regression model #191 based on blood expression levels of the combination of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, each of which normalized against expression levels of IL2RB, can be used to discriminate, with a ROC AUC of at least 0.80 (Table 16), between subjects having colorectal cancer and subjects not having any colorectal pathology. As such, the novel logistic regression model #191 can be used to determine the probability that a test subject has colorectal cancer as opposed to not having any colorectal pathology, based on blood levels of expression of ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and/or VNN1 normalized to those of IL2RB.

Example 7 Determination of the Probability that a Test Subject has Colorectal Cancer as Opposed to not Having Colorectal Cancer Using Blood Levels of RNA Encoded by the Colorectal Cancer Markers: ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 Normalized to those of IL2RB

A blood sample from a test subject is analyzed for levels of RNA encoded by ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1 as described in Example 1, above, thereby generating test data. Logistic regression model #191 of Table 16 is applied to the test data, thereby providing the probability that the test subject has colorectal cancer as opposed to not having any colorectal pathology.

All patents, patent applications, and published references cited herein are hereby incorporated by reference in their entirety.

One skilled in the art will appreciate readily that the invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those objects, ends and advantages inherent herein. The present examples, along with the methods, procedures, treatments, molecules, and specific compounds described herein are presently representative of preferred embodiments, are exemplary, and are not intended as limitations on the scope of the invention. Changes therein and other uses will occur to those skilled in the art which are encompassed within the spirit of the invention as defined by the scope of the claims.

While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims. 

1. A kit comprising packaging and containing, for each gene of a set of two or more genes selected from the group consisting of ACTB, ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1, a primer set capable of generating an amplification product of DNA complementary to RNA encoded, in a human subject, only by the gene.
 2. The kit of claim 1, further containing two or more components selected from the group consisting of a thermostable polymerase, a reverse transcriptase, deoxynucleotide triphosphates, nucleotide triphosphates and enzyme buffer.
 3. The kit of claim 1, further containing at least one labeled probe capable of selectively hybridizing to either a sense or an antisense strand of the amplification product.
 4. The kit of claim 1, further containing a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying a mathematical model to test data representing a level of RNA encoded by the gene in blood of a human test subject, wherein the mathematical model is derived from positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and from negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein the mathematical model is for determining a probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data, and wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.
 5. The kit of claim 1, further containing a computer-readable medium having instructions stored thereon that are operable when executed by a computer for applying, to test data representing a level of RNA encoded by the gene in blood of a human test subject and to negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, a mathematical formula for generating a value indicating, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, and, for IL2RB, whether the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein, for ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6 and VNN1, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer, and wherein, for IL2RB, an indication by the value that the level of RNA encoded by the gene in blood of the test subject is lower than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.
 6. The primer set of claim 1, wherein the set of genes consists of IL2RB and PRRG4.
 7. The primer set of claim 1, wherein the set of genes consists of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1.
 8. A method of determining a probability that a human test subject has colorectal cancer as opposed to not having colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by the gene in blood of the test subject, thereby generating test data; (b) providing positive control data representing levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and providing negative control data representing levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) determining a probability that the test data corresponds to the positive control data and not to the negative control data, wherein the probability that the test data corresponds to the positive control data and not to the negative control data represents the probability that the test subject has colorectal cancer as opposed to not having colorectal cancer.
 9. The method of claim 8, further comprising determining levels of RNA encoded by the gene in blood of a population of human subjects having colorectal cancer, thereby providing the positive control data representing the levels of RNA encoded by the gene in blood of human control subjects having colorectal cancer, and determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer.
 10. The method of claim 8, wherein the determining of the probability that the test data corresponds to the positive control data and not to the negative control data is effected by applying to the test data a mathematical model derived from the positive control data and from the negative control data, and wherein the mathematical model is for determining the probability that data representing a level of RNA encoded by the gene corresponds to the positive control data and not to the negative control data.
 11. A method of classifying a human test subject as more likely to have colorectal cancer than to not have colorectal cancer, the method comprising, for each gene of a set of one or more genes selected from the group consisting of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1: (a) determining a level of RNA encoded by a CLEC4D gene in blood of the test subject, thereby generating test data; (b) providing negative control data representing a level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer; and (c) applying to the test data and to the negative control data a mathematical formula for generating a value indicating whether the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer, wherein an indication by the value that the level of RNA encoded by the gene in blood of the test subject is higher than the level of RNA encoded by the gene in blood of human control subjects not having colorectal cancer classifies the test subject as more likely to have colorectal cancer than to not have colorectal cancer.
 12. The method of claim 11, further comprising determining levels of RNA encoded by the gene in blood of a population of human subjects not having colorectal cancer, thereby providing the negative control data representing the levels of RNA encoded by the gene in blood of human control subjects not having colorectal cancer.
 13. The method of claim 8, wherein the set of genes consists of IL2RB and PRRG4.
 14. The method of claim 8, wherein the set of genes consists of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1.
 15. The method of claim 8, wherein the determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject.
 16. The method of claim 8, wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject.
 17. The method of claim 11, wherein the set of genes consists of IL2RB and PRRG4.
 18. The method of claim 11, wherein the set of genes consists of ANXA3, CLEC4D, IL2RB, LMNB1, PRRG4, TNFAIP6 and VNN1.
 19. The method of claim 11, wherein the determining of the level of RNA encoded by the gene in blood of the test subject is effected by determining the level of RNA encoded by the gene in a blood sample isolated from the test subject.
 20. The method of claim 11, wherein the level of RNA encoded by the gene in blood of the test subject is determined as a ratio to a level of RNA encoded by IL2RB in blood of the test subject. 